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Deep Learning Approach for Extreme Multi-label Text Classification
 
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Extreme classification is a rapidly growing research area focusing on multi-class and multi-label problems involving an extremely large number of labels. Many applications have been found in diverse areas ranging from language modeling to document tagging in NLP, face recognition to learning universal feature representations in computer vision, gene function prediction in bioinformatics, etc. Extreme classification has also opened up a new paradigm for ranking and recommendation by reformulating them as multi-label learning tasks where each item to be ranked or recommended is treated as a separate label. Such reformulations have led to significant gains over traditional collaborative filtering and content-based recommendation techniques. Consequently, extreme classifiers have been deployed in many real-world applications in industry. This workshop aims to bring together researchers interested in these areas to encourage discussion and improve upon the state-of-the-art in extreme classification. In particular, we aim to bring together researchers from the natural language processing, computer vision and core machine learning communities to foster interaction and collaboration. Find more talks at https://www.youtube.com/playlist?list=PLD7HFcN7LXReN-0-YQeIeZf0jMG176HTa
Views: 10877 Microsoft Research
Database Lesson #8 of 8 - Big Data, Data Warehouses, and Business Intelligence Systems
 
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Dr. Soper gives a lecture on big data, data warehouses, and business intelligence systems. Topics covered include big data, the NoSQL movement, structured storage, the MapReduce process, the Apache Cassandra data model, data warehouse concepts, multidimensional databases, business intelligence (BI) concepts, and data mining,
Views: 82079 Dr. Daniel Soper
Mega-R1. Rule-Based Systems
 
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MIT 6.034 Artificial Intelligence, Fall 2010 View the complete course: http://ocw.mit.edu/6-034F10 Instructor: Mark Seifter In this mega-recitation, we cover Problem 1 from Quiz 1, Fall 2009. We begin with the rules and assertions, then spend most of our time on backward chaining and drawing the goal tree for Part A. We end with a brief discussion of forward chaining. License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
Views: 28104 MIT OpenCourseWare
BADM 5.4 K-Means Clustering
 
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This video was created by Professor Galit Shmueli and has been used as part of blended and online courses on Business Analytics using Data Mining. It is part of a series of 37 videos, all of which are available on YouTube. For more information: http://www.dataminingbook.com https://www.twitter.com/gshmueli https://www.facebook.com/dataminingbook Here is the complete list of the videos: • Welcome to Business Analytics Using Data Mining (BADM) • BADM 1.1: Data Mining Applications • BADM 1.2: Data Mining in a Nutshell • BADM 1.3: The Holdout Set • BADM 2.1: Data Visualization • BADM 2.2: Data Preparation • BADM 3.1: PCA Part 1 • BADM 3.2: PCA Part 2 • BADM 3.3: Dimension Reduction Approaches • BADM 4.1: Linear Regression for Descriptive Modeling Part 1 • BADM 4.2 Linear Regression for Descriptive Modeling Part 2 • BADM 4.3 Linear Regression for Prediction Part 1 • BADM 4.4 Linear Regression for Prediction Part 2 • BADM 5.1 Clustering Examples • BADM 5.2 Hierarchical Clustering Part 1 • BADM 5.3 Hierarchical Clustering Part 2 • BADM 5.4 K-Means Clustering • BADM 6.1 Classification Goals • BADM 6.2 Classification Performance Part 1: The Naive Rule • BADM 6.3 Classification Performance Part 2 • BADM 6.4 Classification Performance Part 3 • BADM 7.1 K-Nearest Neighbors • BADM 7.2 Naive Bayes • BADM 8.1 Classification and Regression Trees Part 1 • BADM 8.2 Classification and Regression Trees Part 2 • BADM 8.3 Classification and Regression Trees Part 3 • BADM 9.1 Logistic Regression for Profiling • BADM 9.2 Logistic Regression for Classification • BADM 10 Multi-Class Classification • BADM 11 Ensembles • BADM 12.1 Association Rules Part 1 • BADM 12.2 Association Rules Part 2 • Neural Networks: Part I • Neural Networks: Part II • Discriminant Analysis (Part 1) • Discriminant Analysis: Statistical Distance (Part 2) • Discriminant Analysis: Misclassification costs and over-sampling (Part 3)
Views: 572 Galit Shmueli
Import Data, Analyze, Export and Plot in Python
 
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A common task in data science is to analyze data from an external source that may be in a text or comma separated value (CSV) format. By importing the data into Python, data analysis such as statistics, trending, or calculations can be made to synthesize the information into relevant and actionable information. This demonstrates how to import data, perform a basic analysis such as average values, trend the results, save the figure, and export the results to another text file.
Views: 49267 APMonitor.com
mod01lec02
 
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Views: 18700 Data Mining - IITKGP
HOW TO ANALYZE PEOPLE ON SIGHT - FULL AudioBook - Human Analysis, Psychology, Body Language
 
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How To Analyze People On Sight | GreatestAudioBooks 🎅 Give the gift of audiobooks! 🎄 Click here: http://affiliates.audiobooks.com/tracking/scripts/click.php?a_aid=5b8c26085f4b8&a_bid=ec49a209 🌟SPECIAL OFFERS: ► Free 30 day Audible Trial & Get 2 Free Audiobooks: https://amzn.to/2Iu08SE ...OR: 🌟 try Audiobooks.com 🎧for FREE! : http://affiliates.audiobooks.com/tracking/scripts/click.php?a_aid=5b8c26085f4b8 ► Shop for books & gifts: https://www.amazon.com/shop/GreatestAudioBooks How To Analyze People On Sight | GreatestAudioBooks by Elsie Lincoln Benedict & Ralph Pain Benedict - Human Analysis, Psychology, Body Language - In this popular American book from the 1920s, "self-help" author Elsie Lincoln Benedict makes pseudo-scientific claims of Human Analysis, proposing that all humans fit into specific five sub-types. Supposedly based on evolutionary theory, it is claimed that distinctive traits can be foretold through analysis of outward appearance. While not considered to be a serious work by the scientific community, "How To Analyze People On Sight" makes for an entertaining read. . ► Follow Us On TWITTER: https://www.twitter.com/GAudioBooks ► Friend Us On FACEBOOK: http://www.Facebook.com/GreatestAudioBooks ► For FREE SPECIAL AUDIOBOOK OFFERS & MORE: http://www.GreatestAudioBooks.com ► SUBSCRIBE to Greatest Audio Books: http://www.youtube.com/GreatestAudioBooks ► BUY T-SHIRTS & MORE: http://bit.ly/1akteBP ► Visit our WEBSITE: http://www.GreatestAudioBooks.com READ along by clicking (CC) for Caption Transcript LISTEN to the entire book for free! Chapter and Chapter & START TIMES: 01 - Front matter -- - 00:00 02 - Human Analysis - 04:24 03 - Chapter 1, part 1 The Alimentive Type - 46:00 04 - Chapter 1, part 2 The Alimentive Type - 1:08:20 05 - Chapter 2, part 1 The Thoracic Type - 1:38:44 06 - Chapter 2, part 2 The Thoracic Type - 2:10:52 07 - Chapter 3, part 1 The Muscular type - 2:39:24 08 - Chapter 3, part 2 The Muscular type - 3:00:01 09 - Chapter 4, part 1 The Osseous Type - 3:22:01 10 - Chapter 4, part 2 The Osseous Type - 3:43:50 11 - Chapter 5, part 1 The Cerebral Type - 4:06:11 12 - Chapter 5, part 2 The Cerebral Type - 4:27:09 13 - Chapter 6, part 1 Types That Should and Should Not Marry Each Other - 4:53:15 14 - Chapter 6, part 2 Types That Should and Should Not Marry Each Other - 5:17:29 15 - Chapter 7, part 1 Vocations For Each Type - 5:48:43 16 - Chapter 7, part 2 Vocations For Each Type - 6:15:29 #audiobook #audiobooks #freeaudiobooks #greatestaudiobooks #book #books #free #top #best #psychology This video: Copyright 2012. Greatest Audio Books. All Rights Reserved. Audio content is a Librivox recording. All Librivox recordings are in the public domain. For more information or to volunteer visit librivox.org. Disclaimer: As an Amazon Associate we earn from qualifying purchases. Your purchases through Amazon affiliate links generate revenue for this channel. Thank you for your support.
Views: 2114249 Greatest AudioBooks
Solid Shapes for Kids | #aumsum
 
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Solid Shapes. Objects that occupy space are called solid shapes. Their surfaces are called faces. Faces meet at edges and edges meet at vertices. Some examples of solid shapes: Cone, Cuboid, Sphere, Cylinder, Cube. Cube has 6 faces which are equal squares, 12 equal edges and 8 vertices. Cuboid has 6 rectangular faces where opposite faces are equal. It has 12 edges and 8 vertices. Cylinder has three faces. Two of them are flat while the third one is curved. Cone has 2 faces. One of them is flat and circular while the other is curved. Cone has one circular edge and one vertex. Sphere has neither any edges nor vertices. It has only one curved surface.
Views: 4273362 It's AumSum Time
Philosopher to Data Analyst / Strategy Consultant
 
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Learn Advanced Data Analytics www.DataStrategyWithJonathan.com Martin Chan http://linkedin.com/in/martin-chan-tc 3:24 Tools for Survey Analytics 5:23 The Importance of Reproducibility 8:50 RQDA 11:28 16k R Packages 14:53 Opensource 20:25 The value of Community 26:05 Transitioning from Excel to R Programming 30:55 Learning to Code 37:18 Scalability 44:00 Statistics 49:00 When to use Excel vs R Programming 52:49 RMarkdown 1:02:00 Different Philosophies 1:06:00 Don't show code to stakeholders 1:08:00 Power Point is like time down the drain 1:12:40 Functions and Gists 1:15:00 Make your own package 1:24:00 No Code tools to help you get started with coding Learn how non coders can learn to code using tools like Excel VBA and R Tidyverse. Build flexible reports with R Shiny Flexdashboard R Packages mentioned in this video - Data Analysis: tidyverse (dplyr, tidyr, ggplot2) (06:25) - Qualitative Analysis: RQDA (09:02) Learn more about RQDQ at Martins Blog https://martinctc.github.io/blog/a-short-r-package-review-rqda/ - Combining R and Python in RStudio: reticulate (22:04) - Outputs: rmarkdown (52:55):, flexdashboard (55:44) - Automating PowerPoint: mschart, officer (59:23) - Point-and-click "coding": ggplotAssist, esquisse (1:27:17) Hilary Parker's blog on writing R package from scratch - on cats! (1:15:25) https://hilaryparker.com/2014/04/29/writing-an-r-package-from-scratch/ Hadley Wickham's talk on "You can't do data science in a GUI" (1:28:05) https://speakerdeck.com/hadley/you-cant-do-data-science-in-a-gui
Views: 682 Jonathan Ng
Rihanna - Umbrella (Orange Version) ft. JAY-Z
 
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Get Rihanna’s eighth studio album ANTI now: Download on TIDAL: http://smarturl.it/downloadANTI Stream on TIDAL: http://smarturl.it/streamANTIdlx Download on iTunes: http://smarturl.it/dlxANTI Download on Google Play: http://smarturl.it/ANTIdlxgp Download on Amazon: http://geni.us/amzANTI Music video by Rihanna performing Umbrella. (C) 2007 The Island Def Jam Music Group
Views: 475810833 RihannaVEVO
Analyzing Text Data with Google Sheets and Cloud Natural Language (Cloud Next '18)
 
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Some of the most valuable insights for businesses come from free-form user feedback, but text data can be difficult to process and summarize in a scalable way. This session will show how to use Cloud Natural Language to open up opportunities for analyzing qualitative feedback alongside quantitative data. I’ll show you how to use Google Forms to collect feedback, Google Sheets and Cloud Natural Language to analyze it, and Data Studio to visualize the insights; a powerful yet lightweight solution! Event schedule → http://g.co/next18 Watch more Collaboration & Productivity sessions here → http://bit.ly/2LldTsw Next ‘18 All Sessions playlist → http://bit.ly/Allsessions Subscribe to the Google Cloud channel! → http://bit.ly/NextSub
Views: 4117 G Suite
Datasets: Different Formats
 
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Datasets: Different Formats
Views: 5290 Social Networks
BigQuery Tips: Nested and Repeated Fields and How GOJEK Builds Data Warehouses (Cloud Next '19)
 
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Gain expert advice on BigQuery to take advantage of data warehousing. In this session, GOJEK, a global company with multiple products and services and lots of data, will share how they have designed their data model to have BigQuery and Google Cloud Storage for their data lake and data warehouse, how they've set up their infrastructure using GCP, and how they've built internal tools as part of this process. GOJEK will also share how they govern their data warehouse to support their business, accelerate their decision making process, and gain intelligence about their products. You will also get an in-depth walk through on how to work with semi-structured data, including how to ingest JSON array data types inside of BigQuery. But while denormalizing your schema into a single table with nested and repeated fields can yield performance improvements, the SQL syntax for working with array data can be tricky. Follow along as we demo loading, querying, troubleshooting, and unnesting various semi-structured data sets. Build with Google Cloud → https://bit.ly/2TWjsxq Watch more: Next '19 Data Analytics Sessions here → https://bit.ly/Next19DataAnalytics Next ‘19 All Sessions playlist → https://bit.ly/Next19AllSessions Subscribe to the GCP Channel → https://bit.ly/GCloudPlatform Speaker(s): Evan Jones, Gaurav Anand, Zaki Indra Sukma Session ID: DA205 product:BigQuery,Cloud for Marketing; fullname:Gaurav Anand,Evan Jones;
Pivot Data warehouse Overview
 
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Pivot student data warehouse system for school improvement.
Views: 1113 fivestartechsolution
World of Dinosaurs - National Geographic Documentary HD
 
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Most people think of dinosaurs as big, ferocious and extinct reptiles. That's largely true, but there are some misconceptions. Dinosaurs came in all shapes and sizes. Dinosaurs were the largest land animals of all time, but a great number of dinosaurs were smaller than a turkey. Dinosaurs first appeared between 247 and 240 million years ago. They ruled the Earth for about 175 million years until an extinction event 65.5 million years ago wiped out all of them, except for the avian dinosaurs. Scientists don't agree entirely on what happened, but the extinction likely was a double or triple whammy involving an asteroid impact, choking chemicals from erupting volcanoes, climate change and possibly other factors. Flying on Only the big, classic dinosaurs are extinct. Birds are living dinosaurs, most experts believe. Think of that next time a pigeon strafes you. Fossils show that some of the more advanced dinosaurs had feathers or feather-like body covering, but many of them didn't fly and probably didn't even glide. Archaeopteryx, which was for a long time considered to be the first bird (although this status is not certain), could likely launch itself from the ground, but probably couldn't fly far, according to unpublished research presented at the 2016 Society of Vertebrate Paleontology meeting in Salt Lake City, Utah. Instead, feathers, likely helped these bird-like dinosaurs stay warm as juveniles or send signals to other individuals. Many people think extinct flying reptiles called pterosaurs were dinosaurs. They were dinosaurs' closest relatives, but technically not dinosaurs. Pterosaurs had hollow bones, relatively large brains and eyes, and, of course, the flaps of skin extending along their arms, which were attached to the digits on their front hands. The family includes Pterodactyls, with elaborate, bony head crests and lack of teeth. Pterosaurs survived up until the mass die-off 65 million years ago, when they were going the way of the dodo along with marine reptiles and other nonavian dinosaurs. Hip check Dinosaur fossils were first recognized in the 19th century. In 1842, paleontologist Richard Owen coined the term dinosaur, derived from the Greek deinos, meaning "terrible" or "fearfully great," and sauros, meaning "lizard" or reptile." Scientists classify dinosaurs into two orders — Saurischians and Ornithischians— based on the structure of the bones in their hips. (This saurischian and ornithischian grouping is now disputed. See the "Family tree update" section below to learn more.) Most of the well-known dinosaurs — including Tyrannosaurus rex, Deinonychus and Velociraptor — fall into the order known as Saurischian dinosaurs (pronounced sor-ISK-ee-en). These "reptile-hipped" dinosaurs have a pelvis that points forward, similar to more primitive animals. They are often long-necked, have large and sharp teeth, long second fingers, and a first finger that points strongly away from the rest of the fingers. Saurischians are divided into two groups – four legged herbivores called sauropods and two-legged carnivores called theropods (living birds are in the theropod lineage). Theropods walked on two legs and were carnivorous. "Theropod" means "beast-footed" and they are some of the fearsome and most recognizable dinosaurs — including Allosaurus and T. rex. Scientists have wondered whether large theropods — such as Giganotosaurus and Spinosaurus — actively hunted their prey, or simply scavenged carcasses. The evidence points to the animals working together as opportunistic hunters: they would bring down prey, but also eat animals that were lying around. When fossil-hunters found bones with bite marks on them, they wondered if theropods engaged in cannibalism. It appears now that the animals may have scavenged their own kind, but they didn't hunt down their own. Sauropods were herbivores with long heads, long necks, and long tails. They were among the largest land animals ever, but they likely had small brains. The gentle giants like leaf-eating Apatosaurus, Brachiosaurus and Diplodocus are part of this family. Ornithischia Ornithischian (pronounced or-neh-THISK-ee-en) dinosaurs, a group that includes horned and frilled Triceratops, spiked Stegosaurus and armored Ankylosaurus, are more mild-mannered, plant eaters. These dinosaurs were beaked herbivores. Smaller than the sauropods, the Ornithischia (meaning "bird-hipped") often lived in herds and were prey to the larger species of dinosaurs. Interestingly, the Ornithischia shifted from a two-legged to a four-legged posture at least three times in their evolutionary history and scientists think they could adopt both postures early in their evolutionary history.
Views: 462295 ADVEXON TV
Making AI real with SQL Server Azure databases and Azure big data analytics services - GS005
 
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Are you interested in learning how data and AI can transform your business? If so, this is a ‘must see’ session for you. Be the first to learn about the latest innovations in Microsoft’s Data and AI platform, including SQL Server, Azure SQL Database, Azure Cosmos DB, Azure SQL Data Warehouse, Azure Data Factory and Azure Databricks. Come see our latest demos showcasing the new innovation and learn how these products and services can help you modernize your entire data estate, across on-premises and in the cloud, to help you transform your business with AI-driven insights. Also hear firsthand from customers like Shell, Komatsu, Symantec and Anheuser Busch about their digital transformation journeys using Microsoft’s Data and AI platform. Learn more about Azure AI, databases, and big data analytics: Azure AI platform: https://azure.com/ai Azure SQL Database: https://azure.com/sqldatabase Azure Cosmos DB: https://azure.com/cosmosdb Azure SQL Data Warehouse: https://azure.com/sqldw Azure Data Factory: https://azure.com/adf Azure Databricks: https://azure.com/databricks
Views: 1041 Microsoft Ignite
Yelawolf - Till It’s Gone (Official Music Video)
 
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iTunes: http://smarturl.it/TillItsgone Sign up for updates: http://smarturl.it/Yelawolf.News Music video by Yelawolf performing Till It’s Gone. (C) 2014 Interscope Records Best of Yelawolf: https://goo.gl/vy7NZQ Subscribe here: https://goo.gl/ynkVDL #Yelawolf #TillItsGone #Vevo #HipHop #OfficialMusicVideo
Views: 93514737 YelawolfVEVO
Counting Word Frequency using a Dictionary (Chapter 9)
 
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http://www.py4e.com - Python for Everybody: Exploring Data in Python 3.0 Please visit the web site to access a free textbook, free supporting materials, as well as interactive exercises.
Views: 31081 Chuck Severance
Machine Learning | Chicago Crime
 
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See Ken Litton present his culminating capstone project after 12 weeks of a data science immersive course with General Assembly.
Views: 136 Ken Litton
SFI Community Lecture - Michelle Girvan
 
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Harnessing Chaos and Predicting the Unpredictable with Artificial Intelligence In recent years, machine learning methods such as "deep learning" have proven enormously successful for tasks such as image classification and voice recognition. Despite their effectiveness for big-data classification problems, these methods have had limited success predicting "chaotic" systems like those we see in weather, solar activity, and even brain dynamics. For decades, scientists have understood that the "butterfly effect" makes long-term prediction impossible for these chaotic systems. In this SFI Communty Lecture, physicist Michelle Girvan discusses how a Reservoir Computer (RC) — a special kind of artificial neural network — can draw on its own internal chaotic dynamics in order to forecast systems like the weather, far beyond the time horizon of other methods. The RC provides a knowledge-free approach because it builds forecasts purely from past measurements without any specific knowledge of the system dynamics. By building a new approach that judiciously combines the knowledge-free prediction of the RC with a knowledge-based model, she demonstrates a further, dramatic, improvement in forecasting chaotic systems. Michelle Girvan is an Associate Professor in the Department of Physics and the Institute for Physical Science and Technology at the University of Maryland, College Park. She is also a member of the External Faculty at the Santa Fe Institute. Her research operates at the intersection of statistical physics, nonlinear dynamics, and computer science and has applications to social, biological, and technological systems. _ Learn more at https://santafe.edu Follow us on social media: https://twitter.com/sfiscience https://instagram.com/sfiscience https://facebook.com/santafeinstitute https://facebook.com/groups/santafeinstitute https://linkedin.com/company/santafeinstitute
Views: 1868 Santa Fe Institute
Data and Predictive Analytics: Moneyball in Hollywood w Legendary Entertainment (CXOTalk #276)
 
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The movie industry has adopted "moneyball" techniques, based on data and analytics, to drive box office success. Join CXOTalk host Michael Krigsman in conversation with analytics pioneer, Matthew Marolda, to explore how Legendary Entertainment uses analytics to drive box office success. For more information and to read the complete transcript, see https://www.cxotalk.com/episode/moneyball-movies-data-analytics-legendary-entertainment Matt Marolda is Chief Analytics Officer at Legendary Entertainment, where he started the company's Applied Analytics division, which uses data and analytics to drive strategic decisions across all aspects of the company. Before joining Matt founded StratBridge, which developed software to help many organizations in the NFL, NBA, European Football and Major League Soccer with “moneyball” player analysis, dynamic pricing and revenue analysis.
Views: 6475 CXOTALK
Network Topology (Bangla) | Computer Networking System | HSC ICT Bangla Tutorial
 
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Network Topology (Bangla) | Computer Networking System | HSC ICT Bangla Tutorial. https://www.facebook.com/groups/happyschool24/ HSC ICT students will be very benefited by this bangla tutorial. Happy School always try to present a easy method to understand in a sort time. Here we discuss about Network Topology.. Network topology is very important for data communication and networking system. Here we discuss about Bus, Ring, Star, Tree, Hybrid, Mesh Topology.It is ICT Chapter 2 related. Course Teacher: Oleik Roy Islamic University, Kushtia HSC ICT students are requested to like and then comment your problem. Happy School will give you solution in comment box. Join Our Facebook group for more discussion: https://www.facebook.com/groups/happy... Also Like our page here: https://www.facebook.com/HappySchoolf... HSC ICT students will be very benefited by this bangla tutorial. Happy School always try to present a easy method to understand in a sort time. Course Teacher: Oleik Roy Islamic University, Kushtia HSC ICT students are requested to like and then comment your problem. Happy School will give you solution in comment box. Join Our Facebook group for more discussion: https://www.facebook.com/groups/happyschool24/ Also Like our facebook page here: https://www.facebook.com/HappySchoolforall Please subscribe to our Chanel. Oleik roy is the best ict teacher for hsc students. http://www.bangladesherdiary.com
Views: 32173 Happy School
decision trees
 
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UNH CS 730
Views: 1625 Wheeler Ruml
Peter Bailis: MacroBase, Prioritizing Attention in Fast Data Streams | Talks at Google
 
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Professor Peter Bailis of Stanford provides an overview of his current research project, Macrobase, an analytics engine that provides efficient, accurate, and modular analyses that highlight and aggregate important and unusual behavior, acting as a search engine for fast data. This is part of Google Cloud Advanced Technology Talks, a series dedicated to bringing cutting edge research and prestigious researchers to speak at Google Cloud. All speakers are leading experts and innovators within their given fields of research. Peter Bailis is an assistant professor from Stanford University.
Views: 2369 Talks at Google
Lab 9:  Spatial Analyst Surface Tools for ArcGIS
 
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I created this video with the YouTube Video Editor (http://www.youtube.com/editor)
Views: 13548 Andrew Foy
5 Analytics Techniques You Must Learn Today | Cluster Analysis | Regression Analysis -Great Learning
 
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#Analytics | Know the 5 techniques in analytics which are dominating in the analytics industry and analytics job market. Learn the fundamentals and uses of analytics techniques. The video explains the fundamentals of cluster analysis, regression analysis, conjoint analysis, factor analysis and multiple discriminant analysis. Learn More about our programs: PGP- Business Analytics: https://goo.gl/dWja4e PGP-Big Data Analytics: https://goo.gl/qsg8fo Business Analytics Certificate Program: https://goo.gl/5AnwYy #ClusterAnalysis #RegressionAnalysis #GreatLakes #GreatLearning About Great Learning: - Great Learning is an online and hybrid learning company that offers high-quality, impactful, and industry-relevant programs to working professionals like you. These programs help you master data-driven decision-making regardless of the sector or function you work in and accelerate your career in high growth areas like Data Science, Big Data Analytics, Machine Learning, Artificial Intelligence & more. - Watch the video to know ''Why is there so much hype around 'Artificial Intelligence'?'' https://www.youtube.com/watch?v=VcxpBYAAnGM - What is Machine Learning & its Applications? https://www.youtube.com/watch?v=NsoHx0AJs-U - Do you know what the three pillars of Data Science? Here explaining all about the pillars of Data Science: https://www.youtube.com/watch?v=xtI2Qa4v670 - Want to know more about the careers in Data Science & Engineering? Watch this video: https://www.youtube.com/watch?v=0Ue_plL55jU - For more interesting tutorials, don't forget to Subscribe our channel: https://www.youtube.com/user/beaconelearning?sub_confirmation=1 - Learn More at: https://www.greatlearning.in/ For more updates on courses and tips follow us on: - Google Plus: https://plus.google.com/u/0/108438615307549697541 - Facebook: https://www.facebook.com/GreatLearningOfficial/ - LinkedIn: https://www.linkedin.com/company/great-learning/ - Follow our Blog: https://www.greatlearning.in/blog/ Great Learning has collaborated with the University of Texas at Austin for the PG Program in Artificial Intelligence and Machine Learning and with UT Austin McCombs School of Business for the PG Program in Analytics and Business Intelligence.
Views: 447 Great Learning
Fairness in Machine Learning
 
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Machine learning is increasingly being adopted by various domains: governments, credit, recruiting, advertising, and many others. Fairness and equality are critical aspects, especially in light of anti-discriminatory laws in these domains. Opaque machine learning models: Awareness and mitigation of biases (inherent and perpetuated) is essential. See more on this video at https://www.microsoft.com/en-us/research/video/fairness-machine-learning/
Views: 1257 Microsoft Research
Explanation of Prefix, Suffix and Base words (English and Grammar #1)
 
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An explanation of prefixes, suffixes, base or root words, word stems or stems and how a words meaning changes.
Views: 186130 JoAnn's School
How To Arrange Words In Alphabetical Order | English Grammar | Periwinkle
 
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How To Arrange Words In Alphabetical Order In this video we will learn how to arrange words in alphabetical order. Watch our other videos: English Stories for Kids: https://www.youtube.com/playlist?list=PLC1df0pCmadfRHdJ4Q1IYX58jTNFJL60o English Poems for Kids: https://www.youtube.com/playlist?list=PLC1df0pCmadfdUZWKOgzL_tvEE9gnrO8_ English Grammar for Kids: https://www.youtube.com/playlist?list=PLC1df0pCmadeOXsk1AGM6TgMrIkxLQIGP Hindi Stories: https://www.youtube.com/playlist?list=PLC1df0pCmade3ewXfVcrIdo0os76Epk1d Science Videos: https://www.youtube.com/playlist?list=PLC1df0pCmadfv-D3JU1DiacOsAUhgWGwr For more such videos on English Stories, English Grammar, English Stories, Poem & Rhymes, Hindi Stories and Poems, Maths, Environmental Studies and Science @ https://www.youtube.com/PeriwinkleKids Don't forget to subscribe! Like us on Facebook: https://www.facebook.com/PeriwinkleKids/ Follow us on Twitter: https://twitter.com/Periwinkle_Kids Follow us on Google Plus: https://plus.google.com/+PeriwinkleKids Website: http://www.e-periwinkle.in/
Views: 69207 Periwinkle
XML Basics in SuccessFactors | Role Based Permissions | SuccessFactors tutorial for Beginners
 
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SAP SuccessFactors Training & Certification provided Online from USA industry expert trainers with real time project experience. XML Basics in SuccessFactors | Role Based Permissions | SuccessFactors tutorial for Beginners - This is a video recording of a Live Webinar presentation by our Sr. SAP Solution Architect and trainer who is also a Manager in handling SAP Implementation projects. COURSE PAGE: https://www.zarantech.com/sap-successfactors-training/ REGISTER FOR FREE LIVE DEMO: http://promo.zarantech.com/free-webinar-sap-successfactors/ CONTACT: +1 (515) 309-7846 (or) Email - [email protected] Get More Free Videos - Subscribe ➜ https://goo.gl/5ZqDML "SAP SuccessFactors tutorial" "free SAP SuccessFactors training" "online SAP SuccessFactors training" "Best SAP SuccessFactors training" "SAP SuccessFactors training for Beginners" "Best SAP SuccessFactors Training" Reviews / Testimonials from past trainees are saying: https://goo.gl/ZVfnE4 Refer your friends to ZaranTech - http://www.zarantech.com/be-a-friend-tell-a-friend. -~-~~-~~~-~~-~- Please watch: "High Demand for SAP HANA 2.0 Certified Consultants | HANA 2.0 Training | HANA 2.0 for Beginners" https://www.youtube.com/watch?v=PO7MPIVxEhg -~-~~-~~~-~~-~- Whatsapp: http://bit.ly/2uSFzuJ
Views: 6269 ZaranTech
Subject and Predicate - Learn English Grammar Online
 
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Subject and Predicate - Learn English Grammar with Ranjna Vedhera. Check out https://www.youtube.com/watch?v=r5urt200OIo. One of the best videos on Subject and Predicate SuccessCDs Education ( https://www.youtube.com/successcds1 ) is an online channel focused on providing education through Videos as per CBSE, ICSE and NCERT syllabi upto Class 12 (K-12) for English, Hindi, Science, Social Science, Sanskrit and other subjects. Also visit our Channel for Entrance Exams in India FAQs & Application Process, GK & Current Affairs, Communication Skills and Self Improvement Videos Our website ( https://www.successcds.net ) is one of the leading portal on Entrance Exams and Admissions in India. "About this Video" Subject And Predicate - Learn English Grammar with Ranjna Vedhera. Subject and Predicate In every sentence we mention a person or thing. And then, we say something about that person or thing. The person or thing we mention is the subject. Whatever we say about the person or thing is the predicate. Look at the sentences below 1. The fisher men are catching fish. 2. I live in Mumbai. 3. Lucy is playing piano. In the first sentence 'the fishermen is the subject' and 'are catching fish' is the predicate which tells us what the subject 'the fishermen' is doing. In the second sentence, 'I' is the subject and 'live in Mumbai' is the predicate. In the third sentence, 'Lucy' is the subject is playing piano is the predicate. The Object A predicate may have two parts. A verb and an object The second noun or pronoun in the sentence is called the object. It receives the action of the subject. Let us look at the First and the third sentences again. In the first sentence, fishermen are catching fish. The fishermen is the subject, 'are catching is the action or the verb and fish is the object'. In the third sentence, Lucy is playing piano, Lucy is the 'subject' and the piano is the 'object'. The subject is connected with the object through the verb in a sentence. Both the verb and the object complete the information about the subject. Only a Noun or Pronoun can be an object. Normally a subject comes before the predicate but in some cases such as proverbs it may come at the end of the subject. For Example: Sweet are the uses of adversity. Subject may be missing in imperative sentences. Keep quiet, Sit down, Stand up etc. Exercise - 1 Separate the subject from the predicate in the following sentences: 1. The boy stood on the bank of a river. 2. The princess has a kind heart. 3. I love eating chocolates. 4. I hate dishonesty. 5. Peter is leaving tomorrow. 6. She has been crying all day. Exercise -- 2 Identity the object in the following; also mention when there is no object: 1. Someone has stolen my watch. 2. I miss my childhood. 3. Why are you crying? 4. All living beings are mortal. 5. I am leaving at once. 6. I am leaving this city. 7. The milk is boiling. 8. Lily is boiling milk. For more Such videos watch out https://videos.successcds.net How to learn English online ? Here's how - Check out our English learning videos to learn english Grammar online. You can improve English online by going through our channel Follow us: https://www.facebook.com/SuccessCD https://google.com/+successcds https://twitter.com/entranceexam https://twitter.com/successcds https://www.youtube.com/successcds1 https://www.youtube.com/englishacademy1
Views: 245208 SuccessCDs Education
Lecture 15: Coreference Resolution
 
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Lecture 15 covers what is coreference via a working example. Also includes research highlight "Summarizing Source Code", an introduction to coreference resolution and neural coreference resolution. ------------------------------------------------------------------------------- Natural Language Processing with Deep Learning Instructors: - Chris Manning - Richard Socher Natural language processing (NLP) deals with the key artificial intelligence technology of understanding complex human language communication. This lecture series provides a thorough introduction to the cutting-edge research in deep learning applied to NLP, an approach that has recently obtained very high performance across many different NLP tasks including question answering and machine translation. It emphasizes how to implement, train, debug, visualize, and design neural network models, covering the main technologies of word vectors, feed-forward models, recurrent neural networks, recursive neural networks, convolutional neural networks, and recent models involving a memory component. For additional learning opportunities please visit: http://stanfordonline.stanford.edu/
Teaching Computing in Arts and Humanities
 
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Computing methods are becoming increasingly useful in many areas of humanities and arts. A panel of faculty from both MIT and Cornell University discuss incorporating computing into their teaching. Panel includes: Agustín Rayo, Associate Dean, MIT School of Humanities, Arts, and Social Sciences, and Professor of Philosophy; Alberto Abadie, Associate Director, MIT Institute for Data, Systems, and Society, and Professor of Economics; Michael Scott Cuthbert, Associate Professor of Music at MIT; Erik Demaine, Professor of Computer Science and Electrical Engineering at MIT; Eran Egozy, Professor of the Practice in Music Technology at MIT; and Éva Tardos, Jacob Gould Schurman Professor of Computer Science at Cornell University.   In fields far beyond engineering and science — from political science and urban studies to anthropology and linguistics — some of today’s most exciting new research is fueled by advanced computational capabilities. The MIT Stephen A. Schwarzman College of Computing will create the next generation of highly trained computational thinkers and doers who can offer the world the cultural, ethical, and historical consciousness to use technology for the common good. Watch more videos from MIT: http://www.youtube.com/user/MITNewsOffice?sub_confirmation=1 The Massachusetts Institute of Technology is an independent, coeducational, privately endowed university in Cambridge, Massachusetts. Our mission is to advance knowledge; to educate students in science, engineering, and technology; and to tackle the most pressing problems facing the world today. We are a community of hands-on problem-solvers in love with fundamental science and eager to make the world a better place. The MIT YouTube channel features videos about all types of MIT research, including the robot cheetah, LIGO, gravitational waves, mathematics, and bombardier beetles, as well as videos on origami, time capsules, and other aspects of life and culture on the MIT campus. Our goal is to open the doors of MIT and bring the Institute to the world through video.
How Publishers Can Take Advantage of Machine Learning (Cloud Next '18)
 
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Hearst Newspapers uses Google Cloud Machine Learning infrastructure to automate and create value in the newspaper business. A recent case study has been published detailing this. Also Hearst Newspapers is using TensorFlow to build state-of-the-art recommendation systems. MLAI200 Event schedule → http://g.co/next18 Watch more Machine Learning & AI sessions here → http://bit.ly/2zGKfcg Next ‘18 All Sessions playlist → http://bit.ly/Allsessions Subscribe to the Google Cloud channel! → http://bit.ly/NextSub
How To... Draw a Simple Bar Chart in Excel 2010
 
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Learn one of the most basic operations of Excel - using a Bar Chart to represent your data.
Views: 165238 Eugene O'Loughlin
Zeitgeist Addendum
 
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Please support Peter Joseph's new, upcoming film project: "InterReflections" by joining the mailing list and helping: http://www.interreflectionsmovie.com LIKE Peter Joseph @ https://www.facebook.com/peterjosephofficial FOLLOW Peter Joseph @ https://twitter.com/ZeitgeistFilm * Zeitgeist: Addendum by Peter Joseph. Full movie Sharing this movie is encouraged. Download from www.zeitgeistmovie.com Subtitles provided by Linguistic Team International: http://forum.linguisticteam.org/
Views: 6838975 TZMOfficialChannel
Decision Trees 01 (Python Tutorial) - Find best attribute to split on
 
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Website + download source code @ http://www.zaneacademy.com | Decision Trees 01 w/ JAVA Tutorial @ https://youtu.be/zhY92L2i5AE
Views: 5473 zaneacademy
Auburn Coach Wife Kristi Malzahn Agrees with Match & eHarmony: Men are Jerks
 
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My advice is this: Settle! That's right. Don't worry about passion or intense connection. Don't nix a guy based on his annoying habit of yelling "Bravo!" in movie theaters. Overlook his halitosis or abysmal sense of aesthetics. Because if you want to have the infrastructure in place to have a family, settling is the way to go. Based on my observations, in fact, settling will probably make you happier in the long run, since many of those who marry with great expectations become more disillusioned with each passing year. (It's hard to maintain that level of zing when the conversation morphs into discussions about who's changing the diapers or balancing the checkbook.) Obviously, I wasn't always an advocate of settling. In fact, it took not settling to make me realize that settling is the better option, and even though settling is a rampant phenomenon, talking about it in a positive light makes people profoundly uncomfortable. Whenever I make the case for settling, people look at me with creased brows of disapproval or frowns of disappointment, the way a child might look at an older sibling who just informed her that Jerry's Kids aren't going to walk, even if you send them money. It's not only politically incorrect to get behind settling, it's downright un-American. Our culture tells us to keep our eyes on the prize (while our mothers, who know better, tell us not to be so picky), and the theme of holding out for true love (whatever that is—look at the divorce rate) permeates our collective mentality. Even situation comedies, starting in the 1970s with The Mary Tyler Moore Show and going all the way to Friends, feature endearing single women in the dating trenches, and there's supposed to be something romantic and even heroic about their search for true love. Of course, the crucial difference is that, whereas the earlier series begins after Mary has been jilted by her fiancé, the more modern-day Friends opens as Rachel Green leaves her nice-guy orthodontist fiancé at the altar simply because she isn't feeling it. But either way, in episode after episode, as both women continue to be unlucky in love, settling starts to look pretty darn appealing. Mary is supposed to be contentedly independent and fulfilled by her newsroom family, but in fact her life seems lonely. Are we to assume that at the end of the series, Mary, by then in her late 30s, found her soul mate after the lights in the newsroom went out and her work family was disbanded? If her experience was anything like mine or that of my single friends, it's unlikely. And while Rachel and her supposed soul mate, Ross, finally get together (for the umpteenth time) in the finale of Friends, do we feel confident that she'll be happier with Ross than she would have been had she settled down with Barry, the orthodontist, 10 years earlier? She and Ross have passion but have never had long-term stability, and the fireworks she experiences with him but not with Barry might actually turn out to be a liability, given how many times their relationship has already gone up in flames. It's equally questionable whether Sex and the City's Carrie Bradshaw, who cheated on her kindhearted and generous boyfriend, Aidan, only to end up with the more exciting but self-absorbed Mr. Big, will be better off in the framework of marriage and family. (Some time after the breakup, when Carrie ran into Aidan on the street, he was carrying his infant in a Baby Björn. Can anyone imagine Mr. Big walking around with a Björn?)
Views: 208221 Shari Wing
Best maths basic rule of plus minus into in hindi with tricks and esay
 
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This video is describe PLUS MINUS INTO basic Rules. It is very important part of maths. So watch and enjoy. Plzz suscribe and like. Thanks For watching....
Biological Sequence Analysis II (2010)
 
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January 26, 2010. Andreas Baxevanis, Ph.D. Current Topics in Genome Analysis 2010 Handout: http://www.genome.gov/Pages/Research/IntramuralResearch/DIRCalendar/CurrentTopicsinGenomeAnalysis2010/CTGA2010_Lec03_color.pdf More: http://www.genome.gov/12514286
Electrical Wiring: Electrical circuits wiring tutorial
 
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This Electrical wiring video by http://www.bin95.com shows how to modify an existing motor circuit's electrical wiring using a motor control diagram. This electrical wiring tutorial video is one of the many electrical circuits explored in DVD 4 of the 10 DVD Industrial Electrical Training Video Library. http://www.youtube.com/watch?v=9uMIQycxygQ
Views: 988192 BIN Industrial Training
Building a Recommendation Engine with Machine Learning Techniques (Brian Sam-Bodden) - FSF 2016
 
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In this talk Brian will walk you through the ideas, techniques and technologies used to build a SaaS Recommendation Engine. From building an efficient software classifier, to storing the large amounts of data required, to the pipeline of artificial intelligence and machine learning algorithms used. The system is being built with a myriad of technologies including Java, Cassandra, Ruby, Rails, Clojure, Javascript and more. About the speaker: Brian Sam-Bodden is an author, instructor, speaker and hacker that has spent most of his life (adult and otherwise) crafting software. He is well versed in several programming languages and has a deep passion for Machine Learning and Artificial Intelligence in general. His perfect Sunday includes walks on a virtual beach with his pals of HAL, DeepThought, the Architect and MCP. Brian lives in the post apocalyptic, waste-land, Mad-Max’esque state of Arizona, U.S.A. where he leads Integrallis; a Polyglot Consultancy and is also the founder of Binnacle (http://binnacle.io) a multi-purpose dashboard for web applications. Talk given at Full Stack Fest 2016 (https://www.fullstackfest.com)
Views: 2750 Codegram Technologies
Dilma Rousseff: The Challenges for Democracy in Brazil
 
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This event features Dilma Rousseff, Brazilian past president, in a lecture followed by Q&A at Princeton University on April 13, 2017. Introduction by Pedro Meira Monteiro. English subtitles available (by Charlie Hankin). Co-sponsored by the Department of Spanish and Portuguese, the Program in Latin American Studies and the Princeton Institute for International and Regional Studies. Dilma Rousseff: Os desafios da democracia no Brasil Palestra da ex-presidenta Dilma Rousseff, seguida de debate, na Universidade de Princeton, no dia 13 de abril de 2017. Apresentação: Pedro Meira Monteiro. Organização: Department of Spanish and Portuguese, Program in Latin American Studies, Princeton Institute for International and Regional Studies. For more information: https://spo.princeton.edu/ https://plas.princeton.edu/ http://piirs.princeton.edu/
Views: 1808 Princeton University
InstCon16 | Keeping Track of It All with Canvas Data
 
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Interested in the potential of Canvas Data for your institution? Come see how Hult is using Canvas Data to focus on consistency and compliance across multiple locations and programs. We will take an in-depth look at using Tableau to connect and visualize Canvas Data and the quick ways you can monitor trends in grading, interactions, and set-up across your institution.
Views: 657 CanvasLMS
The Galaxy Primes by E. E. "Doc" Smith
 
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They were four of the greatest minds in the Universe: Two men, two women, lost in an experimental spaceship billions of parsecs from home. And as they mentally charted the Cosmos to find their way back to earth, their own loves and hates were as startling as the worlds they encountered. Chapter 1 - 00:00 Chapter 2 - 1:01:23 Chapter 3 - 1:39:51 Chapter 4 - 2:26:40 Chapter 5 - 3:09:57 Chapter 6 - 4:06:35 Chapter 7 - 4:59:15 Chapter 8 - 5:54:35 Chapter 9 - 6:42:55 Read by: Mark Nelson (https://librivox.org/reader/251)
Views: 4311 Audiobooks Unleashed
Yelawolf - Daddy's Lambo (Official Music Video)
 
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Sign up for updates: http://smarturl.it/Yelawolf.News Music video by Yelawolf performing Daddy's Lambo. (C) 2011 DGC Records Best of Yelawolf: https://goo.gl/vy7NZQ Subscribe here: https://goo.gl/ynkVDL #Yelawolf #DaddysLambo #Vevo #HipHop #OfficialMusicVideo
Views: 52057395 YelawolfVEVO
Lecture - 17 Rule Based Systems II
 
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Lecture Series on Artificial Intelligence by Prof.Sudeshna Sarkar and Prof.Anupam Basu, Department of Computer Science & Engineering,I.I.T, Kharagpur . For more details on NPTEL visit http://nptel.iitm.ac.in.
Views: 13085 nptelhrd
FIX- SIM card removed error- Android/Galaxy Note 4. #28
 
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(HD) (CC) If your phone has a "SIM card removed" error, then DON'T PANIC! This procedure seems to help on many phones but "not all" Android phones. My friend had a problem with his Android which is the same model as mine. (A Samsung Galaxy Note 4). Check out this video. You might get lucky too as my buddy did with his phone. No repairs needed. Fixed in 2 minutes. ALSO...be sure to UPDATE ALL YOUR APPS in the Google Play Store! Do it! UPDATE as of 10 months after this video, NO MORE SIM card errors. This was the fix! Please check out my channel! www.youtube.com/user/northcaledon/videos DISCLAIMER; - WARNING: This video is provided for entertainment and promotional purposes only. It is your responsibility to evaluate the accuracy, instructions and advice contained in this video. No one is liable for any loss or damage caused by your reliance on information contained in this video or in the related comments. Be safe! Anything you try will be done at YOUR OWN RISK!
Views: 143175 Mysimplefix
Web Scraping Best Practices! quick Watch
 
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Python Web Scraping Tutorial 1 (Intro To Web Scraping): site scraper online web scraper php scraper scrape a website screen scraping tools page scraping python web scraping web data scraping scrape website data page scraper screenscraping scrape web page web data scraper internet scraping php web scraping php web scraper html scraper content scraping web harvesting content scraper website scraper tool web scraper tool google scraping scrape website content web screen scraping email scraping scraping web visual web scraper web scraper plus web scrap scraper site web scraping php scraping tools web scraping web pages scrape site open source web scraper web scraping script php screen scraping extract website web scraper open source web scraping free python screen scraping best web scraping tools python scraper extract data from html online scraper website data extractor web scraping companies extract information from website web extraction easy web scraping website data extraction scraper web simple web scraper web scraping tools open source grab data from website web scraper free web page scraping tools web screen scraping tools web scraper python screen scraping php web scraping open source scrape website for data data crawling site scraper tool web page extractor web scraper php best web scrapers price scraping scrape html online screen scraper automated web scraping extract web data website parser scraping the web scrape page google web scraper web scraping software ruby web scraping
Views: 1533 Dinesh Gupta
Lecture 12
 
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This lecture describes the phototrophy in microbial cells.