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Best Laptop for Machine Learning
 
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What kind of laptop should you get if you want to do machine learning? There are a lot of options out there and in this video i'll describe the components of an ideal laptop for ML. I'll also mention the ideal desktop, DIY machine, and cloud option. We'll discuss how RAM, GPUs, CPUs, motherboards, hard drives, and other components affect training and inference time. This video was not sponsored. Only a few days left to signup for my dapps course! https://www.theschool.ai Please Subscribe! And like. And comment. That's what keeps me going. Want more education? Connect with me here: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology instagram: https://www.instagram.com/sirajraval Helpful resources: https://lambdal.com/raw-configurator?product=quad https://www.nvidia.com/en-us/geforce/products/10series/laptops/ https://www.google.com/chromebook/device/acer-chromebook-11/ https://medium.com/yanda/building-your-own-deep-learning-dream-machine-4f02ccdb0460 https://blog.slavv.com/the-1700-great-deep-learning-box-assembly-setup-and-benchmarks-148c5ebe6415 Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ Sign up for the next course at The School of AI: https://www.theschool.ai And please support me on Patreon: https://www.patreon.com/user?u=3191693 Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w Hit the Join button above to sign up to become a member of my channel for access to exclusive content!
Views: 255636 Siraj Raval
Data mining
 
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Data mining (the analysis step of the "Knowledge Discovery in Databases" process, or KDD), an interdisciplinary subfield of computer science, is the computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. The overall goal of the data mining process is to extract information from a data set and transform it into an understandable structure for further use. Aside from the raw analysis step, it involves database and data management aspects, data pre-processing, model and inference considerations, interestingness metrics, complexity considerations, post-processing of discovered structures, visualization, and online updating. The term is a misnomer, because the goal is the extraction of patterns and knowledge from large amount of data, not the extraction of data itself. It also is a buzzword, and is frequently also applied to any form of large-scale data or information processing (collection, extraction, warehousing, analysis, and statistics) as well as any application of computer decision support system, including artificial intelligence, machine learning, and business intelligence. The popular book "Data mining: Practical machine learning tools and techniques with Java" (which covers mostly machine learning material) was originally to be named just "Practical machine learning", and the term "data mining" was only added for marketing reasons. Often the more general terms "(large scale) data analysis", or "analytics" -- or when referring to actual methods, artificial intelligence and machine learning -- are more appropriate. This video is targeted to blind users. Attribution: Article text available under CC-BY-SA Creative Commons image source in video
Views: 1696 Audiopedia
Data Mining College Students
 
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A university police Lieutenant wrote an article in the Chronicle for Higher Education arguing that we should begin collecting massive amounts of personal data of college students. Ana Kasparian and Jayar Jackson discuss on TYT University. https://chronicle.com/article/Mining-Student-Data-Could-Save/129231/
Views: 8346 ThinkTank
Kenneth Cukier: Big data is better data
 
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Self-driving cars were just the start. What's the future of big data-driven technology and design? In a thrilling science talk, Kenneth Cukier looks at what's next for machine learning — and human knowledge. TEDTalks is a daily video podcast of the best talks and performances from the TED Conference, where the world's leading thinkers and doers give the talk of their lives in 18 minutes (or less). Look for talks on Technology, Entertainment and Design -- plus science, business, global issues, the arts and much more. Find closed captions and translated subtitles in many languages at http://www.ted.com/translate Follow TED news on Twitter: http://www.twitter.com/tednews Like TED on Facebook: https://www.facebook.com/TED Subscribe to our channel: http://www.youtube.com/user/TEDtalksDirector
Views: 326591 TED
Text Mining in Publishing
 
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TEXT MINING AND SCHOLARLY PUBLISHING: This short video by John Bond of Riverwinds Consulting discusses Text Mining and the Scholarly Publishing Industry. MORE VIDEOS on TEXT MINING and Scholarly Publishing can be found at: https://www.youtube.com/playlist?list=PLqkE49N6nq3jY125di1g8UDADCMvCY1zk FIND OUT more about John Bond and his publishing consulting practice at www.RiverwindsConsulting.com SEND IDEAS for John to discuss on Publishing Defined. Email him at [email protected] or see http://www.PublishingDefined.com CONNECT Twitter: https://twitter.com/JohnHBond LinkedIn: https://www.linkedin.com/in/johnbondnj Google+: https://plus.google.com/u/0/113338584717955505192 Goodreads: https://www.goodreads.com/user/show/51052703-john-bond YouTube: https://www.youtube.com/c/JohnBond BOOKS by John Bond: The Story of You: http://www.booksbyjohnbond.com/the-story-of-you/about-the-book/ You Can Write and Publish a Book: http://www.booksbyjohnbond.com/you-can-write-and-publish-a-book/about-the-book/ TRANSCRIPT: Hi there. I am John Bond from Riverwinds Consulting and this is Publishing Defined. Today I am going to discuss text mining as it relates to scholarly publishing. Text mining also goes by the phrase text data mining or text analytics. Text mining in scholarly publishing is the process of deriving high-quality information from peer reviewed articles and other content. It does this by processing large amounts of information and looking for patterns within the data, and then evaluating and interpreting the results. Text mining is most beneficial to researchers or other power users of technical content. It is very different from a keyword search such that you might perform with Google. A key word search likely produces thousands of web links with no uniformity in the results and certainly no ability to draw meaningful conclusions. An example: let’s say you are researching bladder cancer in men and you are looking for specific biomarkers for other disease states. You probably don’t have the time to review all the literature you might find through a search at PubMed. Text mining will review the available literature. It understands the parts of speech (nouns, verbs), recognizes abbreviations, takes term frequency into account, and other natural language processes. It will filter through all the content, extracts relevant facts, spot patterns, and provides the researcher with a more condensed set of results and statements than a literature search or a cursory review of abstracts ever could. It knows bladder cancer is a disease state. It knows, in this instance, to look for men as opposed to women. It understands what a biomarker is and how to apply this term to other disease states. It understands bladder cancer is a phrase and not being used as two separate terms. Text mining software involves high level programming and such concepts as word frequency distribution, pattern recognition, information extraction, and natural language processing as well as other programming concepts well beyond the scope of this video. The overall goal is to turn text into data for analysis and thereby help to draw conclusions. However, the results of text mining in and of themselves is not the end product, just part of the process. Individual text mining tools or enterprise level ones have become more common with researchers, librarians, and large for profit and not for profit organizations, and they will only grow. Aside from a text mining tool, an application is also necessary to check that the content being mined is licensed and to provide appropriate links to the content. Text mining is important to publishers or any group that holds large stores of full text articles or databases because this information as a whole has greater value than each individual part. Text mining can help extract that value. A key point for publishers is that the text mining tool and its user, such as a researcher, needs to have access to the content either by it being open access, through a subscription, or through a purchase. Subscription publishers see revenue when content is accessed or purchased. All publishers see article downloads and page views from text mining efforts. Either way, text mining as a tool in research, in medicine, in pharmaceutical R&D will only continue to grow in importance. Well that’s it. Please subscribe to my YouTube channel or click on the playlist to see more videos about text mining in scholarly publishing. And make comments below or email me with questions. Thank so much and take care.
Views: 303 John Bond
Data Mining & Business Intelligence | Tutorial #28 | Naive Bayes Classification (Solved Problem)
 
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Order my books at 👉 http://www.tek97.com/ #RanjiRaj #DataMining #NaiveBayes Follow me on Instagram 👉 https://www.instagram.com/reng_army/ Visit my Profile 👉 https://www.linkedin.com/in/reng99/ Support my work on Patreon 👉 https://www.patreon.com/ranjiraj Watch this video to understand how a problem in Naive Bayes is solved in data mining for classification on the given data set. Watch Now! شاهد هذا الفيديو لفهم كيفية حل مشكلة في Naive Bayes في التنقيب عن البيانات للتصنيف على مجموعة البيانات المحددة. شاهد الآن! Assista a este vídeo para entender como um problema em Naive Bayes é resolvido na mineração de dados para classificação no conjunto de dados fornecido. Assista agora! Regardez cette vidéo pour comprendre comment un problème dans Naive Bayes est résolu dans l'exploration de données pour la classification sur l'ensemble de données donné. Regarde maintenant! Sehen Sie sich dieses Video an, um zu verstehen, wie ein Problem in Naive Bayes im Data Mining zur Klassifizierung auf dem gegebenen Datensatz gelöst wird. Schau jetzt! Mire este video para comprender cómo se resuelve un problema en Naive Bayes en la extracción de datos para su clasificación en un conjunto de datos determinado. ¡Ver ahora! Посмотрите это видео, чтобы понять, как проблема в Naive Bayes решена в области интеллектуального анализа данных для классификации по данному набору данных. Смотри! ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ Add me on Facebook 👉https://www.facebook.com/renji.nair.09 Follow me on Twitter👉https://twitter.com/iamRanjiRaj Read my Story👉https://www.linkedin.com/pulse/engineering-my-quadrennial-trek-ranji-raj-nair Visit my Profile👉https://www.linkedin.com/in/reng99/ Like TheStudyBeast on Facebook👉https://www.facebook.com/thestudybeast/ ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ For more such videos LIKE SHARE SUBSCRIBE Iphone 6s : http://amzn.to/2eyU8zi Gorilla Pod : http://amzn.to/2gAdVPq White Board : http://amzn.to/2euGJ7F Duster : http://amzn.to/2ev0qvX Feltip Markers : http://amzn.to/2eutbZC
Views: 1234 Ranji Raj
Data Mining: How You're Revealing More Than You Think
 
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Data mining recently made big news with the Cambridge Analytica scandal, but it is not just for ads and politics. It can help doctors spot fatal infections and it can even predict massacres in the Congo. Hosted by: Stefan Chin Head to https://scishowfinds.com/ for hand selected artifacts of the universe! ---------- Support SciShow by becoming a patron on Patreon: https://www.patreon.com/scishow ---------- Dooblydoo thanks go to the following Patreon supporters: Lazarus G, Sam Lutfi, Nicholas Smith, D.A. Noe, سلطان الخليفي, Piya Shedden, KatieMarie Magnone, Scott Satovsky Jr, Charles Southerland, Patrick D. Ashmore, Tim Curwick, charles george, Kevin Bealer, Chris Peters ---------- Looking for SciShow elsewhere on the internet? Facebook: http://www.facebook.com/scishow Twitter: http://www.twitter.com/scishow Tumblr: http://scishow.tumblr.com Instagram: http://instagram.com/thescishow ---------- Sources: https://www.aaai.org/ojs/index.php/aimagazine/article/viewArticle/1230 https://www.theregister.co.uk/2006/08/15/beer_diapers/ https://www.theatlantic.com/technology/archive/2012/04/everything-you-wanted-to-know-about-data-mining-but-were-afraid-to-ask/255388/ https://www.economist.com/node/15557465 https://blogs.scientificamerican.com/guest-blog/9-bizarre-and-surprising-insights-from-data-science/ https://qz.com/584287/data-scientists-keep-forgetting-the-one-rule-every-researcher-should-know-by-heart/ https://www.amazon.com/Predictive-Analytics-Power-Predict-Click/dp/1118356853 http://dml.cs.byu.edu/~cgc/docs/mldm_tools/Reading/DMSuccessStories.html http://content.time.com/time/magazine/article/0,9171,2058205,00.html https://www.nytimes.com/2012/02/19/magazine/shopping-habits.html?pagewanted=all&_r=0 https://www2.deloitte.com/content/dam/Deloitte/de/Documents/deloitte-analytics/Deloitte_Predictive-Maintenance_PositionPaper.pdf https://www.cs.helsinki.fi/u/htoivone/pubs/advances.pdf http://cecs.louisville.edu/datamining/PDF/0471228524.pdf https://bits.blogs.nytimes.com/2012/03/28/bizarre-insights-from-big-data https://scholar.harvard.edu/files/todd_rogers/files/political_campaigns_and_big_data_0.pdf https://insights.spotify.com/us/2015/09/30/50-strangest-genre-names/ https://www.theguardian.com/news/2005/jan/12/food.foodanddrink1 https://adexchanger.com/data-exchanges/real-world-data-science-how-ebay-and-placed-put-theory-into-practice/ https://www.theverge.com/2015/9/30/9416579/spotify-discover-weekly-online-music-curation-interview http://blog.galvanize.com/spotify-discover-weekly-data-science/ Audio Source: https://freesound.org/people/makosan/sounds/135191/ Image Source: https://commons.wikimedia.org/wiki/File:Swiss_average.png
Views: 149336 SciShow
Introduction to Process Mining: Turning (Big) Data into Real Value
 
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With process mining, you can make your process visible in less than 5 minutes, based on log data you already have in your IT systems. Learn what process mining is, and how it works, in less than 2 minutes! (Animation work by 908video)
Views: 69837 P2Mchannel
What the Heck Does “Data Science” Really Mean? The Dr. Data Show
 
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In this episode of The Dr. Data Show, Eric Siegel answers the question, "What the heck do 'data science' and 'big data' really mean?" Sign up for future episodes and more info: http://www.TheDoctorDataShow.com Attend Predictive Analytics World: http://www.pawcon.com Read Dr. Data's book: http://www.thepredictionbook.com Welcome to "The Dr. Data Show"! I'm Eric Siegel. “Data science.” “Big data.” What the hell do these buzzwords really, specifically mean? Are they just cockamamie -- intentionally vague jargon that overhypes and overpromises? Or are these terms actually helpful -- do they somehow designate, like, the most profound impact of the Information Age? Well, I’ll start with the vague and overhyping side and then circle back to why these buzzwords may matter after all. It’s time for the Dr. Data buzzword smackdown. There are a lotta problems with these words. First, "data scientist" is redundant. It's like calling a librarian a "book librarian." If you're doing science, it involves data. Duh! Furthermore, don't tell anyone I said this, but real sciences like physics and chemistry don't have "science" in their name. Your science is trying too hard if it has to call itself a science: Social science, political science, data science, and I gotta say -- even though I have three degrees in it and was a professor of it -- computer science is an arbitrarily defined field. It's just the amalgam of everything to do with computers -- as a concept and as an appliance -- from the engineering of how to build them and the deep mathematics about their theoretical limitations to how to make them more user friendly, and even business strategies for managing a team of programmers... Universities might as well also have a "toaster science" department, which covers the engineering of better toasters as well as the culinary arts on how to best cook with them. But I digress. Ok, next buzzword: “Big data.” First of all, it's just grammatically incorrect. It’s like looking at the Pacific Ocean and saying “big water.” It should be “a lotta data” or “plenty of data.” But the real problem with "big data" is that it emphasizes the size. 'Cause what’s exciting about data isn't how much of it there is per se -- it's about how quickly it's growing -- which is amazing by the way. There’s always so much more data today than there was yesterday. So we're gonna run out of adjectives really quickly: “big data,” “bigger data,” “even bigger data,” “the biggest data.” Actually, there’s been a long-running conference called the International Conference on Very Large Databases since 1975. I’m not joking. That's before the first Star Wars movie came out! Now, in some cases, people use the terms data science and big data just to refer to machine learning, i.e., when computers learn from the experience encoded in data. That's the topic of most episodes of this program, The Dr. Data Show. It’s a show about machine learning -- which is a well-defined field and by the way is also often called predictive analytics, especially when you're talking about its deployment in the private or public sector. I would urge folks to use the well-defined terms machine learning or predictive analytics if in fact that's what you’re specifically talking about. But as for data science and big data, in their general usage they suffer from a terrible case of vagueness. The have a wide range of subjective definitions, which compete and conflict. Basically, they're often used to mean nothing more specific than "some clever use of data." The terms don't necessarily refer to any particular technology, method, or value proposition. They're just plain subjective -- you can use them to mean whichever technology you'd like: machine learning, data visualization, or even just basic reporting. But much worse than that, this vagueness often serves to mislead and misrepresent by alluding to capabilities that don't exist. For example, the popular press -- as well certain analytics vendors -- sometimes use "data science" to denote some whole collection of methods that includes machine learning as well as some other advanced methods. The problem is, those other advanced methods are implied but often actually just don't really exist. They're vaporware. This confusion is sometimes inadvertent -- such as when journalists aren’t fully knowledgeable of the topic yet want it to sound as powerful as possible -- but, either way, the end result is souped-up hype that overpromises and circulates misinformation. All these issues, by the way, also apply to the older-school term "data mining," also totally subjective. Besides, calling it "data mining" is like instead of "gold mining," saying “dirt mining.” Malfunction, failed analogy... 'Cause we aren't searching for data, we're searching within data... For the complete transcript and more: http://www.TheDoctorDataShow.com
Views: 874 Eric Siegel
Data Mining: Mastering Data Mining Skills | Part - 2
 
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In this video, Qasim Ali Shah talking on the topic "DATA MINING SKILLS". In this session you will know about the content of trainers. He is giving some useful tips to all students, like: how should you can select your topic to speak effectively and after this what type of content will be helpful for your topic. You will know so many more after watching this video regarding above given topic. ===== ABOUT Qasim Ali Shah ===== Qasim Ali Shah is a Public Speaker- Teacher- Writer- Corporate Trainer & Leader for every age group- Businessmen- Corporate executives- Employees- Students- Housewives- Networkers- Sportsmen and for all who wish everlasting Success- Happiness- Peace and Personal Growth. He helps people to change their belief & thought pattern- experience less stress and more success in their lives through better communication- positive thinking and spiritual knowledge. ===== FOLLOW ME ON THE SOCIALS ===== - Qasim Ali Shah: https://goo.gl/6BKcxu - Google+: https://goo.gl/uPyGvT - Twitter: https://goo.gl/78MVoA - Website : https://goo.gl/Tgjy6u ===== Team Member: Waqas Nasir =====
Views: 8218 Qasim Ali Shah
Fiance Visa Denial due to Social Media Data Mining
 
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http://www.visacoach.com/visa-denial-social-media-data-mining.html USCIS recently hired contractors to research social media to provide additional data for the extreme vetting of Fiance, Spouse and other visa applicants. Expect one’s social media “skeletons” to lead to denial. To Schedule your Free Consultation with Fred Wahl, the Visa Coach visit http://www.visacoach.com/talk.html or Call - 1-800-806-3210 ext 702 or 1-213-341-0808 ext 702 Bonus eBook “5 Things you Must Know before Applying for your Visa” get it at http://www.visacoach.com/five.html Fiancee or Spouse visa, Which one is right for you? http://imm.guru/k1vscr1 What makes VisaCoach Special? Ans: Personally Crafted Front Loaded Presentations. Front Loaded Fiance Visa Petition http://imm.guru/front Front Loaded Spouse Visa Petition http://imm.guru/frontcr1 K1 Fiancee Visa http://imm.guru/k1 K1 Fiance Visa Timeline http://imm.guru/k1time CR1 Spousal Visa http://imm.guru/cr1 CR1 Spouse Visa Timeline http://imm.guru/cr108 Green Card /Adjustment of Status http://imm.guru/gc USCIS recently announced new contracts given to companies to search through social media to collect data on Fiance and other visa applicants. Collection starts October 18. If you have any "suspect" exposure, you have only a few more days to take it down. One of VisaCoach's clients has already experienced denial due to his Facebook presence. This couple's case was as near perfect as we have seen. They were young and in love. They had known each other for a few years and had met more than once. They were evenly matched by age, values and religion. Their "front loaded" petition was awesome and included many solid evidences of their bona fides. The American sponsor even accompanied his fiancé to the interview to demonstrate his sincerity and support for the petition. After a brief interview where the sponsor was not allowed to join in nor asked any questions before, during or after, the consular officer, denied the case. The couple was devastated and confused. What could have gone wrong? A consular officer who exhibits professionalism will state the reasons for denial in writing. And provide this to the rejected applicant immediately, often at the close of the interview itself. You may not agree with the decision, but at least know what it was and then have a starting point for renewed efforts. The officer refused to provide any verbal or written explanation. All the couple had was the fiancee's memory of the interview. I asked her to write a transcript of what happened, to recall exactly what was said and even what the body language was, so that we could study this in an attempt to reconstruct what MIGHT have been in the consular officer’s mind. What seemed odd and out of context, was the consular officer made some comments about "conservative values" and what is a "woman's role in society and in the home". Those comments seemed rather strange at the time and the foreign born fiancé had no idea where those comments came from. Eventually it dawned on us. The American sponsor is active on FaceBook. He is outspoken and his views are somewhat "anti feminist". He had posted on his social media pages, and entered into many online debates, his ideas on conservative values, and HIS ideas about a women's role in the home and society. He is not a bad guy. Not a bad husband. He was just expressing his free speech. He just had some strong views that are not popular, that are not considered "politically correct". The consular officer did her own internet search, found his activity and "Was NOT amused", and denied, putting this loving couple's life's on hold. Was it fair or reasonable that they were denied?. No, I don't think so. Happy end to the story. We took down his Facebook account, reapplied, and six months later they had their visa and began their married life together in Alaska. One random consular officer searching on Facebook ended in a denial. What will happen when ALL Fiance and Spouse applications are accompanied by a detailed dossier of one's online statements, comments jokes, embarrassments, positive and negative feedback from friends or trolls? Expect disaster. Expect many more denials, simply due to exercising a US Citizen's right to free speech. In Conclusion: "Freedom of Speech", doesn't mean freedom to get your visa. The prudent path is prior to applying for a Fiance or Spouse visa to make sure there are no skeletons in your online closet. Clean or temporarily remove, or make private, potentially controversial aspects of your online and public presence before proceeding with your visa application.
Views: 15170 Visa Coach
Bayes theorem trick (solve in less than 30 sec )
 
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Views: 376309 Shrenik Jain
Naive Bayes Classifier Algorithm Example Data Mining | Bayesian Classification | Machine Learning
 
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naive Bayes classifiers in data mining or machine learning are a family of simple probabilistic classifiers based on applying Bayes' theorem with strong (naive) independence assumptions between the features. Naive Bayes has been studied extensively since the 1950s. It was introduced under a different name into the text retrieval community in the early 1960s,and remains a popular (baseline) method for text categorization, the problem of judging documents as belonging to one category or the other (such as spam or legitimate, sports or politics, etc.) with word frequencies as the features. With appropriate pre-processing, it is competitive in this domain with more advanced methods including support vector machines. It also finds application in automatic medical diagnosis. for more refer to https://en.wikipedia.org/wiki/Naive_Bayes_classifier naive bayes classifier example for play-tennis Download PDF of the sum on below link https://britsol.blogspot.in/2017/11/naive-bayes-classifier-example-pdf.html *****************************************************NOTE********************************************************************************* The steps explained in this video is correct but please don't refer the given sum from the book mentioned in this video coz the solution for this problem might be wrong due to printing mistake. **************************************************************************************************************************************** All data mining algorithm videos Data mining algorithms Playlist: http://www.youtube.com/playlist?list=PLNmFIlsXKJMmekmO4Gh6ZBZUVZp24ltEr ******************************************************************** book name: techmax publications datawarehousing and mining by arti deshpande n pallavi halarnkar *********************************************
Views: 42669 fun 2 code
The human insights missing from big data | Tricia Wang
 
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Why do so many companies make bad decisions, even with access to unprecedented amounts of data? With stories from Nokia to Netflix to the oracles of ancient Greece, Tricia Wang demystifies big data and identifies its pitfalls, suggesting that we focus instead on "thick data" -- precious, unquantifiable insights from actual people -- to make the right business decisions and thrive in the unknown. Check out more TED talks: http://www.ted.com The TED Talks channel features the best talks and performances from the TED Conference, where the world's leading thinkers and doers give the talk of their lives in 18 minutes (or less). Look for talks on Technology, Entertainment and Design -- plus science, business, global issues, the arts and more. Follow TED on Twitter: http://www.twitter.com/TEDTalks Like TED on Facebook: https://www.facebook.com/TED Subscribe to our channel: https://www.youtube.com/TED
Views: 103129 TED
6 Books for Improving Your English: Advanced English Lesson
 
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More book recommendations: https://www.speakenglishwithvanessa.com/6-book-recommendations-english-learners/ Download my free e-book: "5 Steps To Becoming A Confident English Speaker" http://www.speakenglishwithvanessa.com/free-ebook --------------------------------------------------------------------- Subscribe and follow on social media! I'd love to meet you! YouTube: http://www.youtube.com/subscription_center?add_user=theteachervanessa Facebook: http://www.facebook.com/speakenglishwithvanessa Google+: https://plus.google.com/+TeacherVanessa/ Send us a postcard from your country: Vanessa Prothe PO Box 104 Asheville, NC 28802 USA --------------------------------------------------------------------- Buy the books in this video! Support yourself and support me! Fantastic Mr. Fox: http://amzn.to/2zcUV0b The Curios Incident of the Dog in the Night: http://amzn.to/2ytEsRO Diary of a Young Girl: http://amzn.to/2AILYxW Harry Potter: http://amzn.to/2ytf9iE Hunger Games: http://amzn.to/2AJKUK4 Chronicles of Narnia: http://amzn.to/2AHddZY Kite Runner: http://amzn.to/2ytjAdr A Thousand Splendid Suns: http://amzn.to/2AZ3taf How to Win Friends and Influence People: http://amzn.to/2ytm4Z0 --------------------------------------------------------------------- Speak English With Vanessa helps English learners to speak American English fluently, naturally, and confidently. To become a fluent English speaker and have English conversations with a native English speaker, go to http://www.speakenglishwithvanessa.com
Lecture - 34 Data Mining and Knowledge Discovery
 
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Lecture Series on Database Management System by Dr. S. Srinath,IIIT Bangalore. For more details on NPTEL visit http://nptel.iitm.ac.in
Views: 134823 nptelhrd
EmoText for opinion mining in long texts
 
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http://socioware.de https://www.researchgate.net/publication/278383087_Opinion_Mining_and_Lexical_Affect_Sensing EmoText for opinion mining in long texts illustrates a domain-independent approach to opinion mining. A thorough description is available in the book "Opinion mining and lexical affect sensing". Empirically revealed that texts should contain not less than 200 words for reliable classification. The engine evaluates features (lexical, stylometric, grammatical, deictic) using different evaluation methods and uses the SMO or NaiveBayes classifiers from the WEKA data mining toolkit for text classification. Statistical EmoText formed a basis for the statistical framework for experimentation and rapid prototyping. The approach was tested on the following English corpora: a Pang corpus with weblogs, Berardinelli movie review corpus with movie reviews, a corpus with spontaneous dialogues (the SAL corpus), and a corpus with product reviews.
Views: 973 Alexander Osherenko
Minecraft - Unnatural Blocks using Book/Chunk Dupe in Java
 
14:22
By using the method to create books that create a chunk that contains too much data that Minecraft can not save, you can create blocks and other items in an unnatural state; headless pistons, floating torches, half beds, and more! This is in version 1.12.2, but has also been verified in versions; 1.8, 1.13.2, 19w04b (1.14 snapshot) - Any version that uses Anvil file Format in Java. My original dupe video: https://youtu.be/sd8SM8YWP9U Earthcomputer's video: https://youtu.be/uw7vEGhKoH8 Earthcomputer's Forge mod links: https://www.youtube.com/redirect?event=video_description&v=uw7vEGhKoH8&q=https%3A%2F%2Fgithub.com%2FEarthcomputer%2Fclientcommands%2Freleases&redir_token=aoQ9SOsJho4VGCcE1ZdczCdC2N98MTU0ODgxNjY0MkAxNTQ4NzMwMjQy EarthComputer's copy paste random pages: https://www.youtube.com/redirect?event=video_description&v=uw7vEGhKoH8&q=https%3A%2F%2Fpastebin.com%2FkREVWL4b&redir_token=aoQ9SOsJho4VGCcE1ZdczCdC2N98MTU0ODgxNjY0MkAxNTQ4NzMwMjQy Yeah Don't Worry's dupe method: https://youtu.be/FuSrlv7qSzQ My custom totem for Minecraft version 1.12.2 or below: http://www.mediafire.com/file/n85wabag4wgee00/BarrenDome_Totem_v2.zip My custom totem for Minecraft version 1.13: http://www.mediafire.com/file/74yjtyrmxfcls2j/BarrenDome%20Totem%201.13%20v1.zip Resource Pack: Faithfulx32 https://faithfulx32.com/ ───────────────────────── ➜ Thank you so much for watching! If you enjoyed, please subscribe, leave a comment, and press that LIKE button! ───────────────────────── ➜ Twitter: www.twitter.com/BarrenDome ───────────────────────── ➜ Discord server: discord.gg/S2sbvKh ───────────────────────── ➜ Contact me: Go to www.youtube.com/user/BarrenDome/about and then click 'send message'. ───────────────────────── ➜ Donate: Want to make a donation, visit: BTC: 187ZA6kTMPZFwm4QvZRRcRvuN7o2tCnD88 or http://www.paypal.me/BarrenDome or https://streamlabs.com/barrendome
Views: 29818 BarrenDome
Top Data Warehouse Interview Questions and Answers
 
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This video talks about Top Data Warehouse Interview Questions and Answers for 2018 Answers to Data Warehouse Interview Questions Top 50 Data Warehouse Interview Questions & Answers Data Warehousing - Interview Questions sql server data warehouse interview questions azure data warehouse interview questions data modeling interview questions and answers Part of SQL Interview Questions and answers Data Warehouse Interview Questions and Answers for 2019 1. What is Datawarehousing? 2. What is data Mining? 3. What is Dimension Table? 4. What is OLAP? 5. What is Materialized view? 6. What is Fact less fact table? 7. What is difference b/w view and materialized view? 8.What is Star schema? 9.Difference b/w star and snowflake schema? 10. Fact table
Views: 3624 Training2SQL MSBI
Is the world getting better or worse? A look at the numbers | Steven Pinker
 
18:33
Was 2017 really the "worst year ever," as some would have us believe? In his analysis of recent data on homicide, war, poverty, pollution and more, psychologist Steven Pinker finds that we're doing better now in every one of them when compared with 30 years ago. But progress isn't inevitable, and it doesn't mean everything gets better for everyone all the time, Pinker says. Instead, progress is problem-solving, and we should look at things like climate change and nuclear war as problems to be solved, not apocalypses in waiting. "We will never have a perfect world, and it would be dangerous to seek one," he says. "But there's no limit to the betterments we can attain if we continue to apply knowledge to enhance human flourishing." Check out more TED Talks: http://www.ted.com The TED Talks channel features the best talks and performances from the TED Conference, where the world's leading thinkers and doers give the talk of their lives in 18 minutes (or less). Look for talks on Technology, Entertainment and Design -- plus science, business, global issues, the arts and more. Follow TED on Twitter: http://www.twitter.com/TEDTalks Like TED on Facebook: https://www.facebook.com/TED Subscribe to our channel: https://www.youtube.com/TED
Views: 810393 TED
What is a HashTable Data Structure - Introduction to Hash Tables , Part 0
 
07:37
This tutorial is an introduction to hash tables. A hash table is a data structure that is used to implement an associative array. This video explains some of the basic concepts regarding hash tables, and also discusses one method (chaining) that can be used to avoid collisions. Wan't to learn C++? I highly recommend this book http://amzn.to/1PftaSt Donate http://bit.ly/17vCDFx STILL NEED MORE HELP? Connect one-on-one with a Programming Tutor. Click the link below: https://trk.justanswer.com/aff_c?offer_id=2&aff_id=8012&url_id=238 :)
Views: 799228 Paul Programming
Data and Goliath: Bruce Schneier on the Hidden Battles to Collect Your Data and Control Your World
 
16:39
http://democracynow.org - Leading security and privacy researcher Bruce Schneier talks about about the golden age of surveillance and his new book, "Data and Goliath: The Hidden Battles to Collect Your Data and Control Your World." The book chronicles how governments and corporation have built an unprecedented surveillance state. While the leaks of Edward Snowden have shed light on the National Security Agency's surveillance practices, less attention has been paid to other forms of everyday surveillance — license plate readers, facial recognition software, GPS tracking, cellphone metadata and data mining Watch Part 2 of this interview: http://www.democracynow.org/blog/2015/3/13/part_2_bruce_schneier_on_the Democracy Now!, is an independent global news hour that airs weekdays on 1,300+ TV and radio stations Monday through Friday. Watch our livestream 8-9am ET: http://democracynow.org Please consider supporting independent media by making a donation to Democracy Now! today: http://democracynow.org/donate FOLLOW DEMOCRACY NOW! ONLINE: Facebook: http://facebook.com/democracynow Twitter: https://twitter.com/democracynow YouTube: http://youtube.com/democracynow SoundCloud: http://soundcloud.com/democracynow Daily Email: http://democracynow.org/subscribe Google+: https://plus.google.com/+DemocracyNow Instagram: http://instagram.com/democracynow Tumblr: http://democracynow.tumblr Pinterest: http://pinterest.com/democracynow iTunes: https://itunes.apple.com/podcast/democracy-now!-audio/id73802554 TuneIn: http://tunein.com/radio/Democracy-Now-p90/ Stitcher Radio: http://www.stitcher.com/podcast/democracy-now
Views: 4118 Democracy Now!
Data Mining with Weka (1.1: Introduction)
 
09:00
Data Mining with Weka: online course from the University of Waikato Class 1 - Lesson 1: Introduction http://weka.waikato.ac.nz/ Slides (PDF): http://goo.gl/IGzlrn https://twitter.com/WekaMOOC http://wekamooc.blogspot.co.nz/ Department of Computer Science University of Waikato New Zealand http://cs.waikato.ac.nz/
Views: 127477 WekaMOOC
Data Preprocessing Steps for Machine Learning & Data analytics
 
03:50
#Pandas #DataPreProcessing #MachineLearning #DataAnalytics #DataScience Data Preprocessing is an important factor in deciding the accuracy of your Machine Learning model. In this tutorial, we learn why Feature Selection , Feature Extraction, Dimentionality Reduction are important. We also learn about the famous methods which can be used for the purpose. Data Preprocessing is a very important step in Data Analytics which is ignored by many. To make your models accurate you have to ensure proper preprocessing as the Machine Learning model is highly dependent on data. For all Ipython notebooks, used in this series : https://github.com/shreyans29/thesemicolon Facebook : https://www.facebook.com/thesemicolon.code Support us on Patreon : https://www.patreon.com/thesemicolon Python for Data Analysis book : http://amzn.to/2oDief8 Pattern Recognition and Machine Learning : http://amzn.to/2p6mD6R
Views: 15734 The Semicolon
12. Clustering
 
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MIT 6.0002 Introduction to Computational Thinking and Data Science, Fall 2016 View the complete course: http://ocw.mit.edu/6-0002F16 Instructor: John Guttag Prof. Guttag discusses clustering. License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
Views: 89964 MIT OpenCourseWare
Mining Your Logs - Gaining Insight Through Visualization
 
01:05:04
Google Tech Talk (more info below) March 30, 2011 Presented by Raffael Marty. ABSTRACT In this two part presentation we will explore log analysis and log visualization. We will have a look at the history of log analysis; where log analysis stands today, what tools are available to process logs, what is working today, and more importantly, what is not working in log analysis. What will the future bring? Do our current approaches hold up under future requirements? We will discuss a number of issues and will try to figure out how we can address them. By looking at various log analysis challenges, we will explore how visualization can help address a number of them; keeping in mind that log visualization is not just a science, but also an art. We will apply a security lens to look at a number of use-cases in the area of security visualization. From there we will discuss what else is needed in the area of visualization, where the challenges lie, and where we should continue putting our research and development efforts. Speaker Info: Raffael Marty is COO and co-founder of Loggly Inc., a San Francisco based SaaS company, providing a logging as a service platform. Raffy is an expert and author in the areas of data analysis and visualization. His interests span anything related to information security, big data analysis, and information visualization. Previously, he has held various positions in the SIEM and log management space at companies such as Splunk, ArcSight, IBM research, and PriceWaterhouse Coopers. Nowadays, he is frequently consulted as an industry expert in all aspects of log analysis and data visualization. As the co-founder of Loggly, Raffy spends a lot of time re-inventing the logging space and - when not surfing the California waves - he can be found teaching classes and giving lectures at conferences around the world. http://about.me/raffy
Views: 25527 GoogleTechTalks
How to find median of a continuous frequency distribution ?
 
07:21
Learn how to find the median of a continuous frequency distribution from this video. To view more Educational content, please visit: https://www.youtube.com/appuseriesacademy To view Nursery Rhymes, please visit: https://www.youtube.com/appuseries To view Content in other Languages, please visit: www.youtube.com/appuseries + "Language". For Example for Hindi content: www.youtube.com/appuserieshindi To Buy Books and CDs, please visit : https://www.appuseries.com
Views: 241623 AppuSeriesAcademy
Welcome to Data-less Decision Making on Analytics Academy
 
01:20
https://analyticsacademy.withgoogle.com Join us for our next course on Analytics Academy: Data-less Decision Making. Learn how to make uninformed business decisions on a whim by following your gut instincts and applying simple guesswork techniques.
Views: 26833 Google Analytics
How To reduce PDF file size Without Quality loss 10MB = 1MB (online & Offline )
 
07:10
Best 5 Mobile Under 10K 1.Redmi 6 Pro (Black, 3GB RAM, 32GB Storage):- https://amzn.to/2WUYQaQ 2.Samsung Galaxy M10 (Charcoal Black, 3+32GB) :- https://amzn.to/2uRGlYZ 3.Honor 7C (Blue, 3GB RAM, 32GB Storage) :- https://amzn.to/2VxdoNJ 4.Samsung Galaxy M10 (Ocean Blue, 2+16GB) :- https://amzn.to/2UISQEK 5.Realme U1 (Brave Blue, 3GB RAM, 32GB Storage) :- https://amzn.to/2uWDxtM Best 5 Mobile Under 15K 1. Samsung Galaxy M30 (Gradation Black, 4+64 GB) :- https://amzn.to/2ULtQg0 2. Samsung Galaxy M20 (Ocean Blue, 4+64GB) :- https://amzn.to/2KhAGpt 3. Honor 8X (Blue, 4GB RAM, 64GB Storage) :- https://amzn.to/2Ki8we8 4. Honor 8X (Blue, 6GB RAM, 64GB Storage) :- https://amzn.to/2YU6HYd 5. Honor Play (Navy Blue, 4GB RAM, 64GB Storage) :- https://amzn.to/2WYVnIx 1.My Tripod for Video Shoot :- https://amzn.to/2uW1BN7 2.Green Screen :- https://amzn.to/2Vx7pIN 3.Mic for Voice Recording :-https://amzn.to/2uRVYQh 4.My Laptop :- https://amzn.to/2Klmps6 5.Light SetUp :- https://amzn.to/2ULwxOA 6.My phone :- https://amzn.to/2OYEdIj 7. Best laptop & Travel bag :- https://amzn.to/2WZrGqP Visit Website and know W/L Ticket & PNR will be confirmed or not - https://www.railtkt.com (जाने आपका टिकट कन्फर्म होगा या नहीं ) -~-~~-~~~-~~-~- My new Govt Jobs Alert Channel Please Support :- https://goo.gl/PuVa2c For Online method please follow link-https://www.sejda.com/compress-pdf Download adobe acrobat- https://acrobat.adobe.com/in/en/free-trial-download.html Follow us on Facebook Page:-https://www.facebook.com/rbtech4u Follow us on Twitter:-https://twitter.com/rbtech4u Subscribe RB-Tech:-https://goo.gl/NbIYtl Watch another PDF Related Video How to Convert PDF to JPEG (Image ) Easily Online & offline-https://youtu.be/Ok5RrnB1LRs How to Combine PDF files into one PDF File . (Online & Offline Easily )-https://www.youtube.com/watch?v=CfODbWwrREY How to convert IRCTC Ticket to PDF IRCTC टिकट को PDF में कैसे सेव करे..?-https://www.youtube.com/watch?v=-tM44z7d-LM Thanks For Watching this video -~-~~-~~~-~~-~- Please watch: "Book IRCTC Ticket on Paytm with Discount ..अब Paytm पे IRCTC से सस्ता टिकट बुक करें " https://www.youtube.com/watch?v=dPo886bTg4I -~-~~-~~~-~~-~-
Views: 410818 RB-Tech
Process Mining Movie: Turning (Big) Data into Real Business Value
 
01:42
With process mining, you can make your process visible in less than 5 minutes, based on log data you already have in your IT systems. This movie shows what process mining is, and how it works, in less than 2 minutes! Animation work by 908video Want to learn more? Also see the website of the IEEE Task Force on Process Mining (http://www.win.tue.nl/ieeetfpm/), the process mining website (www.processmining.org), or the process mining book (http://springer.com/978-3-642-19344-6).
Views: 282 ProcessMiners
How Artificial Intelligence is slowly becoming less art-ificial | Amir Baradaran | TEDxBocaRaton
 
17:22
Imagine a butterfly materializing in the palm of your hand out of thin air. Without truly existing this butterfly has impacted your world- changed your reality. The emerging field of Augmented Reality (AR) intersects art and technology.   Amir is a New York based Iranian-Canadian performance and new media artist. Baradaran’s praxis has inspired academic researchers, art professionals and technology developers alike for its articulation of visual vocabularies that use Augmented Reality (AR) technology around notions of interactivity, data-mining, failed utopias, infiltration and the ephemeral. Baradaran is the recipient of the International Symposium on Mixed and Augmented Reality first place prize and UC Berkeley’s Artist Residency (from Center for New Media, Critical Theory & Race and Gender). The New York Observer, ARTNET, National Public Radio, BBC, Forbes, Art21, Euro-News, Dot429 and Miami New Times have reviewed his work. ARTINFO described his public-art installation, Transient (6,300 NYC taxicabs, 1.5M viewers), as “one of the most interesting urban interventions,” and Franchising Mona Lisa. This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at http://ted.com/tedx
Views: 118584 TEDx Talks
Data and Goliath: The Hidden Battles to Collect Your Data and Control Your World
 
05:37
Leading security and privacy researcher Bruce Schneier talks about about the golden age of surveillance and his new book, "Data and Goliath: The Hidden Battles to Collect Your Data and Control Your World." The book chronicles how governments and corporation have built an unprecedented surveillance state. While the leaks of Edward Snowden have shed light on the National Security Agency’s surveillance practices, less attention has been paid to other forms of everyday surveillance — license plate readers, facial recognition software, GPS tracking, cellphone metadata and data mining. For full episodes of Democracy Now! click the link: http://freespeech.org/collection/democracy-now
Views: 239 freespeechtv
Passive Income: How I make $40,000/year doing nothing (software engineer edition)
 
14:41
Ex-Google Tech lead Patrick Shyu explains passive income, and how he earns additional side-money just by sitting around doing nothing, leveraging his l33t coding skills to develop self-maintaining apps. There are many other areas for passive income as well like Amazon self-publishing eBooks, Bitcoin mining, or drop-shipping. What are your thoughts on passive income? Let's discuss in the comments below! My other projects mentioned in the video: http://panolapse360.com/ http://humanpets.com http://elven.avalancia.com 👕NEW MERCH HERE! http://amazon.com/shop/techlead 👌 SUBSCRIBE 👌 http://youtube.com/techlead?sub_confirmation=1 Video explanations of popular interview questions: http://algoexpert.io/techlead (use code "techlead" for a discount) Get free daily coding interview practice: http://dailycodingproblem.com/techlead Listen to audiobooks to save time on your drive, here's a free book coupon: http://audibletrial.com/techlead Check the tech & camera gear that I'm using (★★★★★): http://amazon.com/shop/techlead My Desk Lamp: https://amzn.to/2D3Zjjt My Mouse: https://amzn.to/2CZwHba My Camera: https://amzn.to/2IlcGPF My Headphones: https://amzn.to/2WU6GBK My Earbuds: https://amzn.to/2VrDiSN My Monitor: https://amzn.to/2I6zseS My Multitool: https://amzn.to/2WSEVt3 My Keyboard: https://amzn.to/2VrE2r3 My Microphone: https://amzn.to/2WYu4OB My Macbook: https://amzn.to/2CZwMeY ‣ For more tech career & interview tips & tricks, check out TechLead: Season 1 Complete HD available for purchase. http://techlead.tech/season1/ http://instagram.com/patrickshyu/ http://twitter.com/patrickshyu/
Views: 838290 TechLead
Data mining
 
32:34
SMOTE - Supersampling Rare Events: Machine Learning with R
 
14:07
Follow me on Twitter @amunategui Check out my new book "Monetizing Machine Learning": https://amzn.to/2CRUO Brief introduction to the SMOTE R package to super-sample/ over-sample imbalanced data sets. SMOTE will use bootstrapping and k nearest neighbor to synthetically create additional observations. Data sets with a target frequency of less than 15% are usually considered as imbalanced/rare. If you liked this video - give me a thumbs up! Thx Companion code on GitHub: https://github.com/amunategui/SMOTE-Oversample-Rare-Events Original SMOTE white paper: https://www.jair.org/media/953/live-953-2037-jair.pdf Follow me on Twitter https://twitter.com/amunategui and signup to my newsletter: http://www.viralml.com/signup.html More on http://www.ViralML.com and https://amunategui.github.io Thanks!
Views: 19259 Manuel Amunategui
1  Introduction to Data Science & Data Analytics - DataHills Srinivas
 
53:17
Online Classes on DATA SCIENCE / DATA ANALYTICS / MACHINE LEARNING with R, PYTHON & WEKA. Good Value for Money - Charged less than any other training institutes. For details Contact: +91 9292005440 or [email protected] INTRODUCTION TO DATA SCIENCE: ============================= What is Data Science? Who is Data Scientist? Who can be Data Scientist? Data Science Process Modern Data Scientist Data Science Workflow Technologies used in Data Science What is DATA SCIENCE : --------------------------------------- Data science is a "concept to statistics, data analysis, machine learning and their related methods" in order to "understand and analyze” with data. Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from data in various forms, both structured and unstructured, similar to data mining. Data Science is also called as "The Sexiest Job of the 21st Century". DATA ANALYSIS: -------------------------- Data analysis is the process of extracting information from data. It involves multiple stages including establishing a data set, preparing the data for processing, applying models, identifying key findings and creating reports. The goal of data analysis is to find actionable insights that can inform decision making. Data analysis can involve data mining, descriptive and predictive analysis, statistical analysis, business analytics and big data analytics. Who is Data Scientist: ------------------------------------ Statistician + Software Engineer A person who is better at statistics than any software engineer or a person who is better at software engineering than any statistician is a data scientist. Who can be Data Scientist: ------------------------------------------ Computing Skills + Mathematics, Probability & Statistical Knowledge + Domain Expertise can be a data scientist Data Science Process: ------------------------------------ Real World - Raw data collected - Data is processed - Clean Data set - Exploratory Data Analysis - Models & Algorithms - Communicate visual report (Making Decisions) - Data Product - Real World Modern Data Scientist: -------------------------------------- Math & Statistics Programming & Database Domain Knowledge & Soft Skills Communication & Visualization Data Science Workflow: -------------------------------------- Problem definition Data Collection & Preparing Model Development Model Deployment Performance Improvement Technologies used in Data Science: --------------------------------------------------------- R Python Weka etc.......
Views: 1501 Data Hills7
Part 2: Bruce Schneier on the Hidden Battles to Collect Your Data and Control Your World
 
14:49
http://democracynow.org - Leading security and privacy researcher Bruce Schneier talks about about the golden age of surveillance and his new book, "Data and Goliath: The Hidden Battles to Collect Your Data and Control Your World." The book chronicles how governments and corporation have built an unprecedented surveillance state. While the leaks of Edward Snowden have shed light on the National Security Agency's surveillance practices, less attention has been paid to other forms of everyday surveillance — license plate readers, facial recognition software, GPS tracking, cellphone metadata and data mining. Watch Part 1 of this interview: http://www.democracynow.org/2015/3/13/data_and_goliath_bruce_schneier_on Democracy Now!, is an independent global news hour that airs weekdays on 1,300+ TV and radio stations Monday through Friday. Watch our livestream 8-9am ET: http://democracynow.org Please consider supporting independent media by making a donation to Democracy Now! today: http://democracynow.org/donate FOLLOW DEMOCRACY NOW! ONLINE: Facebook: http://facebook.com/democracynow Twitter: https://twitter.com/democracynow YouTube: http://youtube.com/democracynow SoundCloud: http://soundcloud.com/democracynow Daily Email: http://democracynow.org/subscribe Google+: https://plus.google.com/+DemocracyNow Instagram: http://instagram.com/democracynow Tumblr: http://democracynow.tumblr Pinterest: http://pinterest.com/democracynow iTunes: https://itunes.apple.com/podcast/democracy-now!-audio/id73802554 TuneIn: http://tunein.com/radio/Democracy-Now-p90/ Stitcher Radio: http://www.stitcher.com/podcast/democracy-now
Views: 1595 Democracy Now!
Statistical Aspects of Data Mining (Stats 202) Day 1
 
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Google Tech Talks June 26, 2007 ABSTRACT This is the Google campus version of Stats 202 which is being taught at Stanford this summer. I will follow the material from the Stanford class very closely. That material can be found at www.stats202.com. The main topics are exploring and visualizing data, association analysis, classification, and clustering. The textbook is Introduction to Data Mining by Tan, Steinbach and Kumar. Googlers are welcome to attend any classes which they think might be of interest to them. Credits: Speaker:David Mease
Views: 216461 GoogleTechTalks
Richest Country Comparison (All 188 Countries Ranking)
 
05:54
An animated comparison of the richest country in the world. All 188 countries ranked according to their National Wealth - how rich are they, and if all their money were to convert to gold, how big will the amount of gold they have relative to the size of a human. Also featuring World's richest person Jeff Bezos who is richer than over 100 countries, and Apple, the richest company, which market capitalization is richer than over 150 countries! Source: Credit Suisse (Global Wealth Data Book 2017) Note: 1) Figures listed refers to National Wealth and NOT GDP!!! National Wealth refers to the cumulative sum of every adult marketable value of financial assets plus non-financial assets (principally housing and land) less debts. 2) All 195 United Nation countries included except for Cape Verde, Nauru, Palestine, St Kitts and Nevis, South Sudan, Tuvalu and Vatican City due to lack of available data. 3) Solid Gold Cube refers to a theoretical 1m by 1m by 1m 100% Gold Cube purchased at the current market price. It does not represent Gold Reserves but rather how much gold can be bought if all national wealth/financial assets were converted into gold. Music Used: Chomatic Fuge - Kevin Macload (incompetech) Featured countries (in order): Sao Tome and Principe, Micronesia, Guinea Bissau, Kiribati, Marshall Islands, Tonga, The Gambia, Vanuatu, Saint Vincent and the Grenadines, Malawi, Sierra Leone, Dominica, Grenada, Comoros, Antigua and Barbuda, Maldives, Burundi, Saint Lucia, Suriname, Belize, Swaziland, Samoa, Central African Republic, Djibouti, Guyana, Mauritania, Solomon Islands, Bhutan, Seychelles, Palau, Fiji, Lesotho, Timor-Leste, Rwanda, Madagascar, Barbados, Mozambique, Guinea, Liberia, Somalia, Chad, Equatorial Guinea, Monaco, Liechtenstein, Republic of Congo, Mali, San Marino, Ethiopia, Tajikistan, Niger, Zambia, Belarus, Eritrea, Montenegro, Togo, Moldova, Syria, Uganda, Bahamas, Ghana, Botswana, Burkina Faso, Nicaragua, Armenia, Brunei, Trinidad and Tobago, Democratic Republic of Congo, Macedonia, Andorra, Gabon, Kyrgyzstan, Benin, Haiti, Jamaica, Senegal, Namibia, Tanzania, Laos, Albania, Mongolia, Zimbabwe, Cameroon, Sudan, Turkmenistan, Bahrain, Papua New Guinea, Bosnia and Herzegovina, Mauritius, Cambodia, Bolivia, Ivory Coast, Afghanistan, Honduras, Nepal, Yemen, Malta, Paraguay, Kenya, Ukraine, Latvia, North Korea, Estonia, Kazakhstan, Serbia, El Salvador, Azerbaijan, Georgia, Panama, Myanmar, Lithuania, Guatemala, Sri Lanka, Jordan, Venezuela, Cyprus, Lebanon, Uruguay, Bulgaria, Costa Rica, Slovenia, Oman, Slovakia, Dominican Republic, Tunisia, Puerto Rico, Ecuador, Uzbekistan, Luxembourg, Iceland, Nigeria, Angola, Cuba, Egypt, Libya, Algeria, Iran, Iraq, Qatar, Morocco, Romania, Bangladesh, Kuwait, Hungary, Vietnam, Thailand, Czech Republic, Malaysia, Peru, Pakistan, Argentina, Philippines, United Arab Emirates, Colombia, Finland, Chile, Portugal, South Africa, Saudi Arabia, Ireland, Poland, Greece, Israel, Turkey, New Zealand, Singapore, Denmark, Norway, Austria, Mexico, Indonesia, Russia, Sweden, Belgium, Brazil, Netherlands, Switzerland, Spain, India, South Korea, Australia, Canada, Italy, France, Germany, United Kingdom, Japan, China, United States
Views: 10353540 Reigarw Comparisons
[ORE] Ship Builds - Fit Theorycrafting - EVE Online Live
 
06:31:40
Tip the show: https://streamelements.com/markeedragon-3970/tip Want an entry on the Live Show Giveaway while the show is live? Get your entry here. https://store.markeedragon.com/index.php?cat=18 We will draw near the end of the live show and the winner will be notified by email. If you are viewing the giveaways while the show is offline only monthly giveaways will appear. http://store.markeedragon.com/affiliate.php?id=4&redirect=index.php?cat=4 Special Viewer Discount or Bonus. YOUR CHOICE! Want a bonus on your EVE new account or Plex? Use the discount code of "discount" and get 3% off your order. Or want 3.3% cash back for even more savings? Use bonus code "bonus" and get 3.3% credit in your account for future purchases This is for a limited time and the discount/bonus codes may be changed or removed at any time. The discount / bonus is provided by Markee Dragon Game Codes and we are an authorized CCP reseller. Codes delivered in 20 minutes or less. Twitter: http://twitter.com/markeedragon Play Money Film: Itunes: https://geo.itunes.apple.com/us/movie/play-money/id1448320260?mt=6&at=1000lRnJ Amazon US: https://amzn.to/2TqabyB Amazon UK: https://www.amazon.co.uk/Play-Money-Richard-Garriott/dp/B07MZBKYPH/ Play Money Book: http://amzn.to/2kVsfTg What's my computer build? Want to know what other stuff I use? Find it here: https://www.amazon.com/shop/markeedragon Want to Try EVE for free? Get it here: http://secure.eveonline.com/signup/?invc=d6baec26-231d-4ced-9cd2-1a8b3713d72d&action=buddy Join us for chat in Discord https://discord.gg/markeedragon Discord is what we use for in game chat and voice comms. This is a simulcast of http://twitch.tv/markeedragon . You can watch here live on YouTube and talk in chat. but for the giveaways mentioned on the show those currently only work in Twitch chat. You do not have to watch on Twitch. You only need to be in the Twitch chat to get in on the giveaways. WTFast is what I use to improve my connection to EVE. I get at least a 20% improvement at all times. Try it here: http://www.wtfast.com/markeedragon Videos How to convert Loyalty Points This video shows how we decided what items to use. Items Sold. https://www.youtube.com/watch?v=rnv4eW9hwP0 What worked Successful conversion of 1m LP to 1.5b ISK in 13 days. https://www.youtube.com/watch?v=eiGEj4XhKt0 Hauling Introduction https://www.youtube.com/watch?v=7NjY9aU-uBQ Hauling is a great secondary income. Market Blue Line Hauling is a great secondary income. EVE Sites Mentioned on the Show EVE Guides and Ship Fits: http://news.markeedragon.com/category/game-guides-how-to/eve-online-guides/ Moose Army Corp - My Null Corp I am a member of. In game channel "MooseArmy" to speak to a recruiter. Airhogs - The best all around corp and great for new players. I am also a member. "Airhogs" channel in game to speak to a recruiter. If you wish to be in my corp for mining you must be in a Hogs corp first. LP Store Conversion See what LP items are currently worth on the market. https://www.fuzzwork.co.uk/lpstore/ Daopa's LP Stores Database LP store items information http://www.ellatha.com/eve/LP-Stores EVE Assets Manager Find your stuff. Know where your money is sitting! http://eve.nikr.net/jeveasset EVE Markets Market history data. http://eve-markets.net/ EVEPraisal Quick values for your loot and other market actions. http://evepraisal.com/ EVE Maps All kinds of map related information. http://evemaps.dotlan.net/ Deepsafe https://deepsafe.xyz Excellent crowed sourced information on cosmic signatures. All explorers should use this. EVE University EVE Wiki http://wiki.eveuniversity.org/Main_Page EVE Workbench. http://www.eveworkbench.com gives you the ability to share your ship fits and more. Live shows Schedule: https://docs.google.com/spreadsheets/d/1zQZoKQnzGRgWXBefzGKlyfDppGQWzJy6PafWm-4c4sQ/pubhtml Music by Monstercat http://www.monstercat.com #eveonline
Views: 1000 markeedragon
Data Mining & Business Intelligence | Tutorial # 29 | Introduction to BI
 
07:39
Order my books at 👉 http://www.tek97.com/ #RanjiRaj #BusinessIntelligence Follow me on Instagram 👉 https://www.instagram.com/reng_army/ Visit my Profile 👉 https://www.linkedin.com/in/reng99/ Support my work on Patreon 👉 https://www.patreon.com/ranjiraj Follow me on Instagram 👉 https://www.instagram.com/reng_army/ Visit my Profile 👉 https://www.linkedin.com/in/reng99/ Support my work on Patreon 👉 https://www.patreon.com/ranjiraj This video will give you an overview of about what Business Intelligence is all about. Watch Now! سيقدم لك هذا الفيديو نظرة عامة حول ما يدور حول ذكاء الأعمال. شاهد الآن ! Это видео даст вам обзор о том, что такое Business Intelligence. Смотри ! Este video le brindará una descripción general sobre de qué se trata Business Intelligence. Ver ahora ! In diesem Video erhalten Sie einen Überblick darüber, worum es bei Business Intelligence geht. Schau jetzt ! Cette vidéo vous donnera un aperçu de ce qu'est la Business Intelligence. Regarde maintenant ! Este vídeo lhe dará uma visão geral sobre o que é o Business Intelligence. Assista agora ! ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ Add me on Facebook 👉https://www.facebook.com/renji.nair.09 Follow me on Twitter👉https://twitter.com/iamRanjiRaj Read my Story👉https://www.linkedin.com/pulse/engineering-my-quadrennial-trek-ranji-raj-nair Visit my Profile👉https://www.linkedin.com/in/reng99/ Like TheStudyBeast on Facebook👉https://www.facebook.com/thestudybeast/ ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ For more such videos LIKE SHARE SUBSCRIBE Iphone 6s : http://amzn.to/2eyU8zi Gorilla Pod : http://amzn.to/2gAdVPq White Board : http://amzn.to/2euGJ7F Duster : http://amzn.to/2ev0qvX Feltip Markers : http://amzn.to/2eutbZC
Views: 764 Ranji Raj
EVE Life is like a Box of Angry Fuel Blocks! - Giveaway - EVE Online Live
 
04:42:03
Tip the show: https://streamelements.com/markeedragon-3970/tip Want an entry on the Live Show Giveaway while the show is live? Get your entry here. https://store.markeedragon.com/index.php?cat=18 We will draw near the end of the live show and the winner will be notified by email. If you are viewing the giveaways while the show is offline only monthly giveaways will appear. http://store.markeedragon.com/affiliate.php?id=4&redirect=index.php?cat=4 Special Viewer Discount or Bonus. YOUR CHOICE! Want a bonus on your EVE new account or Plex? Use the discount code of "discount" and get 3% off your order. Or want 3.3% cash back for even more savings? Use bonus code "bonus" and get 3.3% credit in your account for future purchases This is for a limited time and the discount/bonus codes may be changed or removed at any time. The discount / bonus is provided by Markee Dragon Game Codes and we are an authorized CCP reseller. Codes delivered in 20 minutes or less. Twitter: http://twitter.com/markeedragon Play Money Film: Itunes: https://geo.itunes.apple.com/us/movie/play-money/id1448320260?mt=6&at=1000lRnJ Amazon US: https://amzn.to/2TqabyB Amazon UK: https://www.amazon.co.uk/Play-Money-Richard-Garriott/dp/B07MZBKYPH/ Play Money Book: http://amzn.to/2kVsfTg What's my computer build? Want to know what other stuff I use? Find it here: https://www.amazon.com/shop/markeedragon Want to Try EVE for free? Get it here: http://secure.eveonline.com/signup/?invc=d6baec26-231d-4ced-9cd2-1a8b3713d72d&action=buddy Join us for chat in Discord https://discord.gg/markeedragon Discord is what we use for in game chat and voice comms. This is a simulcast of http://twitch.tv/markeedragon . You can watch here live on YouTube and talk in chat. but for the giveaways mentioned on the show those currently only work in Twitch chat. You do not have to watch on Twitch. You only need to be in the Twitch chat to get in on the giveaways. WTFast is what I use to improve my connection to EVE. I get at least a 20% improvement at all times. Try it here: http://www.wtfast.com/markeedragon Videos How to convert Loyalty Points This video shows how we decided what items to use. Items Sold. https://www.youtube.com/watch?v=rnv4eW9hwP0 What worked Successful conversion of 1m LP to 1.5b ISK in 13 days. https://www.youtube.com/watch?v=eiGEj4XhKt0 Hauling Introduction https://www.youtube.com/watch?v=7NjY9aU-uBQ Hauling is a great secondary income. Market Blue Line Hauling is a great secondary income. EVE Sites Mentioned on the Show EVE Guides and Ship Fits: http://news.markeedragon.com/category/game-guides-how-to/eve-online-guides/ Moose Army Corp - My Null Corp I am a member of. In game channel "MooseArmy" to speak to a recruiter. Airhogs - The best all around corp and great for new players. I am also a member. "Airhogs" channel in game to speak to a recruiter. If you wish to be in my corp for mining you must be in a Hogs corp first. LP Store Conversion See what LP items are currently worth on the market. https://www.fuzzwork.co.uk/lpstore/ Daopa's LP Stores Database LP store items information http://www.ellatha.com/eve/LP-Stores EVE Assets Manager Find your stuff. Know where your money is sitting! http://eve.nikr.net/jeveasset EVE Markets Market history data. http://eve-markets.net/ EVEPraisal Quick values for your loot and other market actions. http://evepraisal.com/ EVE Maps All kinds of map related information. http://evemaps.dotlan.net/ Deepsafe https://deepsafe.xyz Excellent crowed sourced information on cosmic signatures. All explorers should use this. EVE University EVE Wiki http://wiki.eveuniversity.org/Main_Page EVE Workbench. http://www.eveworkbench.com gives you the ability to share your ship fits and more. Live shows Schedule: https://docs.google.com/spreadsheets/d/1zQZoKQnzGRgWXBefzGKlyfDppGQWzJy6PafWm-4c4sQ/pubhtml Music by Monstercat http://www.monstercat.com #eveonline
Views: 978 markeedragon
TriUnity Series with Dr. Shmuel Asher- Episode 6: Simulacrum-Building the Perfect Beast
 
02:33:54
TriUnity Series Ep. 6 - Is the massive NSA Data collection: A Means for crating a carbon copy reality? Dr. Asher's website: http://ancienthebrewlearningcenter.bl... Soul Revolution, The Book: https://www.createspace.com/5958835 Simulacrum A simulacrum is a representation or imitation of a person or thing. The word was first recorded in the English language in the late 16th century, used to describe a representation, such as a statue or a painting, especially of a god. By the late 19th century, it had gathered a secondary association of inferiority: an image without the substance or qualities of the original. Soul hijacking inside and outside “time lines” Dr. Eben Alexander: http://www.ebenalexander.com/ The application of language, how English is an artificially constructed language of spellcraft; law and legal terms as deceptions to gain tactic consent. Key concepts of soul memory of storage and retrieval; Learning as an ongoing work; memory organization to allow recall as needed. The process of narrative building, modification, and distortion. Souls programmed during Between Lives “Soul School” classes. MEDICAL/MENTAL ISSUES: implants, negative phobias, mental illness, psychopathy, etc. hidden behind a programmed “wall”. 49:00 - Sexual identity conflicts, or “re-gendered souls”: Souls are not male or female, but both (hermaphrodite); each soul takes on memory via DNA. Archons drop in false narratives related to gender identity. So-called “gay” people are dropped into bodies opposite to the soul’s gender identity; the LIE that people are “born this way”, OR the religious oppression of gay people as being perverse/“evil”. 1:00:00 - NSA Surveillance and Data Mining: Massive data collection via NSA: WHY are they gathering data at this level of granularity? Intimate data Bulk collection, way beyond the ability of humans to analyze and usefully deploy. Big data center in Utah, now a new, larger one at Ft. Meade, MD. Ray Kurzweil, Bill Joy, and others, talking about removing consciousness from soul, and uploading to another “reality”/holoverse. Arguments for a usurped “prison planet” matrix as excuse to consent to upload to the “new” matrix. Camera at Walmart everywhere. Walmart as a processing center for government logistics; underground tactical operations. TSA body scanners creating data for human image (avatar) replication inside an artificial matrix construct. CERN and Antarctica as ruses to push fear memes and the Nazi BS cover stories for their secret occult Archon operations. The solution is to be DIVERGENT—Do NOT Consent. Quantum computing, the DWave computer and the undefinable meaning of “quantum”. Is it really “AI”? The False Population Proposition: 7 billion people on Earth? Is what lives here, not ALL are “human”. Soul-less humans? Black science re-animation projects, soul transplantation, and insertion of artificial/dark souls. Google Glass, Occulus Rift, other immersive technologies which build Soul Cages. or an eternal looping reality which is cut off from Original Source. Dr. Asher discusses the myths, delusions, and ignorance of “Judeo-Chrisitanity”; “Keeping it simple: Truth comes in levels and is actually simple: The Everlasting Agreement. 10,000 Lies—-Or ONE Truth?
Views: 4696 OffPlanet Media
2019 CR1 Visa Timeline for Spouse visa to USA
 
09:23
http://www.visacoach.com/cr1-visa-timeline.html Before you decide on the spouse visa path, it is essential you understand just how long it will take before you make any irrevocable decisions or actions. Many of my clients were shocked and surprised after they returned from their honeymoon to start the visa process to find out not only is the spouse visa slower than a Fiance Visa, but in fact the time it takes is measured in years not months or weeks. To Schedule your Free Case Evaluation with Fred Wahl, the Visa Coach visit http://www.visacoach.com/talk.html or Call - 1-800-806-3210 ext 702 or 1-213-341-0808 ext 702 Bonus eBook “5 Things you Must Know before Applying for your Visa” get it at http://www.visacoach.com/five.html Fiancee or Spouse visa, Which one is right for you? http://imm.guru/k1vscr1 What makes VisaCoach Special? Ans: Personally Crafted Front Loaded Presentations. Front Loaded Fiance Visa Petition http://imm.guru/front Front Loaded Spouse Visa Petition http://imm.guru/frontcr1 K1 Fiancee Visa http://imm.guru/k1 K1 Fiance Visa Timeline http://imm.guru/k1time CR1 Spousal Visa http://imm.guru/cr1 CR1 Spouse Visa Timeline http://imm.guru/cr108 Green Card /Adjustment of Status http://imm.guru/gc How long does it take to get a CR1 Spouse visa? As of 2019, the answer is 14 to 18 months on average. 6 to 8 months USCIS 5 to 7 months NVC 2 to 3 months Consulate I regularly get calls from people saying those numbers must be wrong, because they found a website or person who promised a MUCH shorter processing time so what's their secret? Well the secret is they are either telling you what "you want to hear" so they can get your money, or just referring to one step of the process, not ALL the steps from initial submission of your petition, to visa embossed onto your spouse's passport When I give time estimates I always use what is relevant to the couple, and that is starting from the day USCIS receives the petition, ending on the day your foreign spouse gets the visa. Two different departments of the US government are involved, USCIS (homeland security) and the Department of State. From Mid 2017 through now Homeland Security recently is getting their job done relatively slowly, currently taking 6 to 8 months. (this compares to processing times of a 2 to 3 months years ago) Why is USCIS now taking 2 to 3 times as long? I call this the Trump Effect. President Trump after taking office in January 2017 has mandated that USCIS vigorously enforce and administer immigration laws, take no short cuts. The goal is to restrict Legal immigration while stopping illegal immigration. "We have to get much tougher, much smarter, and less politically correct," Trump said. What this means is that they are very closely examining and scrutinizing all cases looking for reasons to deny. In addition cases that regularly had their interviews waived now specifically there is an Executive order that no interviews regardless of the strength of their evidences, may be waived. The result is USCIS has more work to do, has more bases to touch in the processing of EACH case. And while President Trump has promised to hire more staff to handle the increased load, so far no new staff has been hired, but the workload has increased. This is the Trump Effect. More work, with same staff. The result is that USCIS processing times for spouse visas have stretched to take at least 6 to 8 months. And it is possible this may even get worse, depending on how many new steps USCIS is asked to take, such as "extreme vetting" and "social media data mining" that are new labor intensive steps that have been proposed but not implemented yet. USCIS Processing includes a background check by the FBI In addition to the general slow down due to the "Trump Effect" what also affects how long it takes for USCIS to approve your case is a function of how complete your petition is, how busy the processing center is, how current your FBI file is, and a bit of luck. The most obvious source of added delay is caused by incomplete and sloppy petitions. When USCIS finds a problem, processing grinds to a halt, and it is stopped until the problem is fixed. Sometimes the errors are so big that they don't bother asking for corrections and simply deny a case outright. Once USCIS finishes their part, the case is passed to the US Department of State. The Department of State has a processing center in New Hampshire, called the National Visa Center or NVC. NVC has now completely revised the way spouse visas are processed there. Previously one submitted a hard copy package of civil and financial documents for NVC to review. Now NVC has instituted a fully online system where all documents are submitted electronically over the Internet. So far this system has been fairly buggy. With frequent technical outages and problems.
Views: 2747 Visa Coach
Why Vegetarians Miss Fewer Flights:  Five Bizarre Insights from Data – The Dr. Data Show
 
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In this episode of The Dr. Data Show, Eric Siegel reveals five bizarre insights found in data. Sign up for future episodes and more info: http://www.TheDoctorDataShow.com Attend Predictive Analytics World: http://www.pawcon.com Read Dr. Data's book: http://www.thepredictionbook.com It’s weird: Vegetarians miss fewer flights. It’s wacky: People who like "curly fries" on Facebook are more intelligent. You're traveling through a dimension whose boundaries are that of imagination. Well, it’s not really The Twilight Zone, but let's call it "The 'Freakonomics' of big data," or "The Ripley’s Believe It or Not of data science." We live in a weird and wacky world, full of bizarre and surprising connections, and these connections are reflected within all those tons of data constantly being collected. That's what makes data the world's most potent, flourishing "unnatural resource." And so the world has enthusiastically dived into a golden age of data discoveries. A frenzy of number-crunching is churning out a heap of insights that are colorful, sometimes surprising, and often valuable. So, I'm gonna explain how this works, and investigate five bizarre discoveries found in data. Now, the whole point of computers is to have things done automatically -- so why not automate scientific discovery? Well, that is, in fact, often what’s achieved by machine learning, when computers learn from the experience encoded in data. You can think of the learning process in two phases: Number one, find individual insights like the one about vegetarians. Number two, combine the insights together to improve their capacity to predict -- this is also called “predictive modeling," since you're combining them together into a single model. Now, that's actually a little simplified, 'cause machine learning often interweaves these two phases, but we can think of the first one, the hunt for insights, as a foundational part of the process. Having computers make such discoveries is the very automation of scientific research. This is a major paradigm shift that upends the traditional scientific method, which is to form a hypothesis and then test it. For example, an airline might speculate that passengers who request a vegetarian meal end up missing their flight less often. Then they'd examine data in order to test this hypothesis. By the way, the reason why this is the case for vegetarians is a separate question, which I'll address in a couple minutes -- the first question is simply whether or not this little theory holds true. But, you know, there are so many trends like that you could check for. How about passengers who prefer an aisle seat rather than a window, or passengers traveling from certain cities, etc.? Perhaps those groups are also less likely to miss their flight. We humans are pretty smart, but, instead of sitting around conjecturing on such things, why not just unleash the computer to search through a whole bunch of possible trends to see which turn out to be true? Use your CPU as a hypothesis-testing machine, a "robot scientist." By hunting tirelessly and robotically, no stone is left unturned. The technical terms for doing this include feature selection, or "trying each independent variable one at a time as a univariate model." But whatever you call it, this kind of search process reaches beyond the more limited range of ideas that originate from human hunches. Allow it to do its number-crunching thing and the machine will spit out valuable discoveries -- which sometimes turn out to be unexpected and may seem to defy logic. Now, before you get too excited about a potential "robot scientist," here's an important warning. When you push the "go" button, cranking up the open-ended, massive search for scientific discoveries, it can backfire and get you into major trouble by drawing false conclusions. It might find apparent trends within the data that don't actually hold true in general. The technical word for this pitfall is p-hacking. Actually, you can never ever ever be literally 100% conclusive about a connection found in data -- there's always at least some remote chance the data fooled you, like even if you flip a coin 100 times and it comes up heads every time, there's still some very remote chance it's just a normal coin and you had a crazy long streak of heads. But, with precautions that properly check the conclusions drawn from data -- which apply a high standard of statistical rigor -- we can reduce the odds of being mislead by data down to an acceptably remote long-shot. Alright, let's see what our robot scientist came up with. Here are several connections found in data. Each one helps predict things -- like who will miss a flight, who is more intelligent, and who will prove to be more financially creditworthy -- and so these serve as foundational building blocks with which machine learning builds predictive models. ... For the complete transcript and more: http://www.TheDoctorDataShow.com
Views: 686 Eric Siegel
Steve Lohr: "Data-ism" | Authors at Google
 
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Steve Lohr, a technology reporter for the New York Times, chronicles the rise of Big Data, addressing cutting-edge business strategies and examining the dark side of a data-driven world. Coal, iron ore, and oil were the key productive assets that fueled the Industrial Revolution. Today, Data is the vital raw material of the information economy. The explosive abundance of this digital asset, more than doubling every two years, is creating a new world of opportunity and challenge. Data-ism is about this next phase, in which vast, Internet-scale data sets are used for discovery and prediction in virtually every field. It is a journey across this emerging world with people, illuminating narrative examples, and insights. It shows that, if exploited, this new revolution will change the way decisions are made—relying more on data and analysis, and less on intuition and experience—and transform the nature of leadership and management. Lohr explains how individuals and institutions will need to exploit, protect, and manage their data to stay competitive in the coming years. Filled with rich examples and anecdotes of the various ways in which the rise of Big Data is affecting everyday life it raises provocative questions about policy and practice that have wide implications for all of our lives.
Views: 4840 Talks at Google
The Russ Belville Show #519 Data Mining - Putting Pot Poisonings Into Perspective
 
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While the anti-pot scaremongers keep railing about kids getting into marijuana accidentally, we show how those incidents make up less than 0.13% of all accidental ingestions by toddlers.
Views: 42 Russ Belville
Why is EVERYONE Buying this Tablet?? - Amazon Fire 7
 
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Buy Fire 7 tablet: On Amazon: http://geni.us/7QKiEz On Newegg: http://geni.us/KMIdA Get an unrestricted 30-day free trial of FreshBooks at https://www.freshbooks.com/techtips Sign up for Private Internet Access VPN at https://www.privateinternetaccess.com/pages/linus-tech-tips/linus1 It may not be HD.. It doesn't have the best battery life.. But the Amazon Fire 7 is definitely the best tablet you can get (for $40) so why not? It does Netflix, it has a headphone jack, what more do you want? ( ͡° ͜ʖ ͡°) Discuss on the forum: https://linustechtips.com/main/topic/931725-new-series-why-is-everyone-buying-this-tablet/ Our Affiliates, Referral Programs, and Sponsors: https://linustechtips.com/main/topic/75969-linus-tech-tips-affiliates-referral-programs-and-sponsors Linus Tech Tips merchandise at http://www.designbyhumans.com/shop/LinusTechTips/ Linus Tech Tips posters at http://crowdmade.com/linustechtips Our Test Benches on Amazon: https://www.amazon.com/shop/linustechtips Our production gear: http://geni.us/cvOS Get LTX 2018 tickets at https://www.ltxexpo.com/ Twitter - https://twitter.com/linustech Facebook - http://www.facebook.com/LinusTech Instagram - https://www.instagram.com/linustech Twitch - https://www.twitch.tv/linustech Intro Screen Music Credit: Title: Laszlo - Supernova Video Link: https://www.youtube.com/watch?v=PKfxmFU3lWY iTunes Download Link: https://itunes.apple.com/us/album/supernova/id936805712 Artist Link: https://soundcloud.com/laszlomusic Outro Screen Music Credit: Approaching Nirvana - Sugar High http://www.youtube.com/approachingnirvana Sound effects provided by http://www.freesfx.co.uk/sfx/
Views: 2429674 Linus Tech Tips
Mod-01 Lec-04 Clustering vs. Classification
 
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Pattern Recognition by Prof. C.A. Murthy & Prof. Sukhendu Das,Department of Computer Science and Engineering,IIT Madras.For more details on NPTEL visit http://nptel.ac.in
Views: 21456 nptelhrd

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