• Intro to Algorithms: Crash Course Computer Science #13

    Algorithms are the sets of steps necessary to complete computation - they are at the heart of what our devices actually do. And this isn’t a new concept. Since the development of math itself algorithms have been needed to help us complete tasks more efficiently, but today we’re going to take a look a couple modern computing problems like sorting and graph search, and show how we’ve made them more efficient so you can more easily find cheap airfare or map directions to Winterfell... or like a restaurant or something. Ps. Have you had the chance to play the Grace Hopper game we made in episode 12. Check it out here! http://thoughtcafe.ca/hopper/ CORRECTION: In the pseudocode for selection sort at 3:09, this line: swap array items at index and smallest should be: swap array items at i...

    published: 24 May 2017
  • How To Program For Beginners | Episode 1: Algorithms

    This is the start to a new series, and I hope to teach you guys all the tricks and tips you need to becoming a successful programmer! If you're interested in more videos, and you want to continue to get better at programming, please subscribe for all future episodes!

    published: 30 May 2016
  • How Machines Learn

    How do all the algorithms around us learn to do their jobs? Bot Wallpapers on Patreon: https://www.patreon.com/posts/15959388 Discuss this video: https://www.reddit.com/r/CGPGrey/comments/7klmd3/how_do_machines_learn/ Footnote: https://www.youtube.com/watch?v=wvWpdrfoEv0 Podcasts: https://www.youtube.com/user/HelloInternetPodcast https://www.youtube.com/channel/UCqoy014xOu7ICwgLWHd9BzQ Thank you to my supporters on Patreon: James Bissonette, James Gill, Cas Eliëns, Jeremy Banks, Thomas J Miller Jr MD, Jaclyn Cauley, David F Watson, Jay Edwards, Tianyu Ge, Michael Cao, Caron Hideg, Andrea Di Biagio, Andrey Chursin, Christopher Anthony, Richard Comish, Stephen W. Carson, JoJo Chehebar, Mark Govea, John Buchan, Donal Botkin, Bob Kunz https://www.patreon.com/cgpgrey How neural networks ...

    published: 18 Dec 2017
  • Python Machine Learning Tutorial | Machine Learning Algorithms | Python Training | Edureka

    ( Python Training : https://www.edureka.co/python ) This Edureka Python tutorial (Python Tutorial Blog: https://goo.gl/wd28Zr) gives an introduction to Machine Learning and how to implement machine learning algorithms in Python. Below are the topics covered in this tutorial: 1. Why Machine Learning? 2. What is Machine Learning? 3. Types of Machine Learning 4. Supervised Learning 5. KNN algorithm 6. Unsupervised Learning 7. K-means Clustering Algorithm Check out our playlist for more videos: https://goo.gl/Na1p9G Subscribe to our channel to get video updates. Hit the subscribe button above. #Python #PythonTutorial #PythonMachineLearning #PythonTraining How it Works? 1. This is a 5 Week Instructor led Online Course,40 hours of assignment and 20 hours of project work 2. We have a 24x7 O...

    published: 07 Apr 2017
  • Why The YouTube Algorithm Will Always Be A Mystery

    The mysterious YouTube algorithm. It's confused people for years, and will continue to do so. So why isn't YouTube more transparent? It used to be that they wouldn't tell anyone how it works - but now, it's that they can't. Let's talk about deep learning algorithms, neural networks, and search engine optimisation. CREDITS: Thanks to animator Matt Ley for the wonderful cartoon of me: https://www.youtube.com/user/Thelaserbearguy I put this together in three days, plus a day of checking and proofing, in Adobe After Effects. It took about eight hours to render, but that's because every frame has keying, lighting, camera, and motion blur effects, and because the original footage of me was in 4.6k lossless. Yes, the sound of the black box working is the sound of a microwave (it's the one in ...

    published: 15 May 2017
  • Brian Christian & Tom Griffiths: "Algorithms to Live By" | Talks at Google

    Practical, everyday advice which will easily provoke an interest in computer science. In a dazzlingly interdisciplinary work, acclaimed author Brian Christian and cognitive scientist Tom Griffiths show how the algorithms used by computers can also untangle very human questions. They explain how to have better hunches and when to leave things to chance, how to deal with overwhelming choices and how best to connect with others. From finding a spouse to finding a parking spot, from organizing one's inbox to understanding the workings of memory, Algorithms to Live By transforms the wisdom of computer science into strategies for human living. Brian Christian is the author of The Most Human Human, a Wall Street Journal bestseller, New York Times editors’ choice, and a New Yorker favorite book ...

    published: 12 May 2016
  • Algorithm using Flowchart and Pseudo code Level 1 Flowchart

    Algorithm using Flowchart and Pseudo code Level 1 Flowchart By: Yusuf Shakeel http://www.dyclassroom.com/flowchart/introduction 0:05 Things we will learn 0:21 Level 0:28 Level 1 Flowchart 0:33 Important terms 0:37 Procedure 0:45 Algorithm 0:54 Flowchart 1:00 Pseudo code 1:08 Answer this simple question 1:14 How will you log into your facebook account 1:30 Next question 1:32 Write an algorithm to log into your facebook account 1:44 Algorithm to log in to facebook account in simple English 2:06 Writing Algorithm 2:14 Flowchart 2:16 There are 6 basic symbols that are commonly used in Flowchart 2:20 Terminal 2:27 Input/Output 2:35 Process 2:42 Decision 2:52 Connector 3:00 Control Flow 3:06 All the 6 symbols 3:13 Flowchart rules 3:25 Flowchart exercise 3:28 Add 10 and 20 4:00 Another exerci...

    published: 27 Aug 2013
  • CppCon 2017: Nicholas Ormrod “Fantastic Algorithms and Where To Find Them”

    Presentation Slides, PDFs, Source Code and other presenter materials are available at: https://github.com/CppCon/CppCon2017 — Come dive into some exciting algorithms — tools rare enough to be novel, but useful enough to be found in practice. Want to learn about "heavy hitters" to prevent DOS attacks? Come to this talk. Want to avoid smashing your stack during tree destruction? Come to this talk. Want to hear war stories about how a new algorithm saved the day? Come to this talk! We'll dive into the finest of algorithms and see them in use — Fantastic Algorithms, and Where To Find Them. — Nicholas Ormrod: Facebook, Software Engineer Nicholas is a infrastructure engineer at Facebook. If he talks too much, disable him with a well-placed nerd snipe. — Videos Filmed & Edited by Bash Films: ht...

    published: 27 Oct 2017
  • Ensemble learners

    This video is part of the Udacity course "Machine Learning for Trading". Watch the full course at https://www.udacity.com/course/ud501

    published: 06 Jun 2016
  • Algorithms and Tips You Need to know to Master EPLL

    Hope this video helped! Thanks for watching! Video idea I may or may not continue: Basically, you guys can film yourselves on any event official or unofficial, and you can send in a good solve for YOUR standards. Note: Good reactions will be targeted Then, each month maybe, or 2 months, I'll upload a 'best solves of the month'. Featuring your videos. What defines best? Just an interesting solve of yours, maybe an event your good at, maybe an official solve, and good reactions will be fun to watch. How to send in videos: Nothing fancy, just upload to youtube public or unlisted and private message me a link to it. Or if you really want, you can just send the link here in the comments. Now remember, I'm not sure I will continue this series, I just want to see how successful and entertainin...

    published: 06 Apr 2017
  • Sorting in Python || Learn Python Programming (Computer Science)

    Sorting is a fundamental task in software engineering. In Python, there are a variety of ways to sort lists, tuples, and other objects. Today we talk about the sort() method which is an in-place algorithm for sorting lists. We also cover the sorted() function which can be used on more objects, and creates a sorted copy, leaving the original object unchanged. We were able to make this Python video with the help of our Patrons on Patreon! We would like to recognize the generosity of our VIP Patrons Matt Peters, Andrew Mengede, Martin Stephens, and Markie Ward. Thank you so much for helping us continue our work! ➢➢➢➢➢➢➢➢➢➢ To​ ​help​ us continue making videos,​ ​you​ ​can​ ​support​ Socratica at: ​Patreon​: https://www.patreon.com/socratica Socratica Paypal: https://www.paypal.m...

    published: 08 Oct 2017
  • Computational Thinking: Algorithm Design

    This video introduces the concept of Algorithm Design in Computational Thinking. It is part of a short course to introduce Middle and High School teachers to Computational Thinking. Learn more at http://www.curriki.org/oer/Algorithm-Design-101423/?mrid=101147

    published: 02 Mar 2016
  • Algorithms: Graph Search, DFS and BFS

    Learn the basics of graph search and common operations; Depth First Search (DFS) and Breadth First Search (BFS). This video is a part of HackerRank's Cracking The Coding Interview Tutorial with Gayle Laakmann McDowell. http://www.hackerrank.com/domains/tutorials/cracking-the-coding-interview?utm_source=video&utm_medium=youtube&utm_campaign=ctci

    published: 27 Sep 2016
  • How to Figure Out the Day of the Week For Any Date Ever

    To learn more about Brilliant, go to https://brilliant.org/BeSmart/ and sign up for free. First 200 people will get 20% off the annual Premium subscription. ↓↓↓ More info and sources below ↓↓↓ You can be a human computer too. Our cheat sheet: http://bit.ly/2rftqkv Want to go NEXT LEVEL? Learn how to adjust for Julian calendar and BC dates You might think that computers are the only things that run algorithms, but you’re wrong. Here’s a neat mental trick for calculating the day of the week for any day ever, developed by famous mathematician John H. Conway Don’t miss our next video! SUBSCRIBE! ►► http://bit.ly/iotbs_sub READ MORE: https://en.wikipedia.org/wiki/Doomsday_rule Martin Gardner, "The Universe in a Handkerchief: Lewis Carroll's Mathematical Recreations, Games, Puzzles, ...

    published: 16 Jan 2018
  • Predicting Stock Price Mathematically

    There are two prices that are critical for any investor to know: the current price of the investment he or she owns, or plans to own, and its future selling price. Despite this, investors are constantly reviewing past pricing history and using it to influence their future investment decisions. Some investors won't buy a stock or index that has risen too sharply, because they assume that it's due for a correction, while other investors avoid a falling stock, because they fear that it will continue to deteriorate. http://www.garguniversity.com Check out Ebook "Mind Math" from Dr. Garg https://www.amazon.com/MIND-MATH-Learn-Math-Fun-ebook/dp/B017QEIF18

    published: 07 Nov 2015
  • YouTube Algorithm 2017 Explained - The A.I. Behind The Curtain

    Here is part of my CVXLive 2017 Presentation: YouTube Algorithm 2017 Explained - The A.I. Behind The Curtain. This is the 3rd part of the Decoding the YouTube Algorithm and learn how to grow fast on YouTube with Algorithm Driven views series. Learn about YouTube Machine Learning Technology and how it interacts with viewers, videos, and channels. Get Access to Free VidSummit Replays https://vidsummit.com/freereplays Tickets to VidSummit 2017 https://vidsummit.com Decoding the YouTube Algorithm and learn how to grow fast on YouTube with Algorithm Driven views series ➜ https://goo.gl/sa6aGp Get More Great Tips - Subscribe ➜ http://goo.gl/dWNo9H Share this Video: ➜ https://youtu.be/Ix1gnDmuMyI My Favorite YouTube Tool TubeBuddy Download TubeBuddy Free Today! ➜ http://derral.link/tubebudd...

    published: 09 Aug 2017
  • 12. Clustering

    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

    published: 19 May 2017
  • Ethereum Games Explained

    Crypto-kitties! I'm going to cover the most important parts of the popular crypto-kitties game built on the Ethereum blockchain in this video. The game is over 2000 lines of Solidity code and it allows players to buy, sell, and breed these collectible cats. At one point, this game accounted for a third of transactions on the Ethereum network which is absolutely insane. This is a great example of a wildly popular use case for a decentralized application. There is a lot of potential here to make a game that people obsess over and makes both the creators and players a good amount of money. Enjoy! Code for this video: https://github.com/llSourcell/Cryptokitties Please Subscribe! And like. And comment. That's what keeps me going. Want more education? Connect with me here: Twitter: https://t...

    published: 13 Apr 2018
  • Gradient descent, how neural networks learn | Chapter 2, deep learning

    Subscribe for more (part 3 will be on backpropagation): http://3b1b.co/subscribe Thanks to everybody supporting on Patreon. https://www.patreon.com/3blue1brown http://3b1b.co/nn2-thanks For any early stage ML startup founders, Amplify Partners would love to hear from you via 3blue1brown@amplifypartners.com To learn more, I highly recommend the book by Michael Nielsen http://neuralnetworksanddeeplearning.com/ The book walks through the code behind the example in these videos, which you can find here: https://github.com/mnielsen/neural-networks-and-deep-learning MNIST database: http://yann.lecun.com/exdb/mnist/ Also check out Chris Olah's blog: http://colah.github.io/ His post on Neural networks and topology is particular beautiful, but honestly all of the stuff there is great. And if...

    published: 16 Oct 2017
  • 'The Algorithm' - How YouTube Search & Discovery Works

    Welcome to this series of videos on how YouTube's search & discovery system works. In this first installment, we talk about how our 'algorithm' follows the audience. WATCH THE NEXT VIDEO: https://goo.gl/SJiwDS GO TO THE LESSON: https://goo.gl/qV5PgY SUBSCRIBE: https://goo.gl/So4XIG With over 400 hours of video uploaded every minute, that can be a challenge. YouTube’s recommendation systems provide a real-time feedback loop to cater to each viewer and their varying interests. It learns from over 80 billion bits of feedback from the audience, daily, to understand how to serve the right videos to the right viewers at the right time. Our goal is to get people to watch more videos that they enjoy, so that they come back to YouTube regularly. Creators often ask, “What kind of videos does the ...

    published: 28 Aug 2017
  • But what *is* a Neural Network? | Chapter 1, deep learning

    Subscribe to stay notified about new videos: http://3b1b.co/subscribe Support more videos like this on Patreon: https://www.patreon.com/3blue1brown Special thanks to these supporters: http://3b1b.co/nn1-thanks For any early-stage ML entrepreneurs, Amplify Partners would love to hear from you: 3blue1brown@amplifypartners.com Full playlist: http://3b1b.co/neural-networks Typo correction: At 14:45, the last index on the bias vector is n, when it's supposed to in fact be a k. Thanks for the sharp eyes that caught that! For those who want to learn more, I highly recommend the book by Michael Nielsen introducing neural networks and deep learning: https://goo.gl/Zmczdy There are two neat things about this book. First, it's available for free, so consider joining me in making a donation Nie...

    published: 05 Oct 2017
  • 2018 Website Trends: AI Algorithms

    In terms of the web and the evolution of it, content has become much more focused on you as an individual. Currently, he sites you go to for news show a dashboard that is most pertinent to you and your social feeds are catered and customized exactly for you. In 2018, websites in general are going to begin to do more of this. In order to make content more personal, machine learning and artificial intelligence algorithms will be relied on more often. This will create a more personal experience, serving up the most engaging and appropriate content for each user. This will really come into the limelight throughout 2018. And, it will continue to advance in 2019 and the years that follow. For more 2018 website trends, visit: https://www.yokoco.com/2018/01/16/2018-website-trends/ In this video...

    published: 22 Jan 2018
  • What Are Algorithms in Data Analytics - Data Science Jargon for Beginners

    In this video i am going to explain what algorithms are in data analytics and how data analysts and data scientists use algorithms to extract data from big data databases. ► Full Playlist Explaining Data Jargon ( https://www.youtube.com/playlist?list=PL_9qmWdi19yDhnzqVCAhA4ALqDoqjeUOr ) ► http://jobsinthefuture.com/index.php/2017/11/23/what-are-algorithms-in-data-analytics-data-science-jargon-for-beginners/ Trying to make sense of the big data industry? Make sure you know your terms if you want to keep your head above water earn a data career. There is a lot of technical jargon floating around the data science industry and over the past week I have been defining some of these key terms to help you make better sense as you develop your interest and understanding of the industry. What ar...

    published: 23 Nov 2017
  • Cognition: How Your Mind Can Amaze and Betray You - Crash Course Psychology #15

    You can directly support Crash Course at http://www.subbable.com/crashcourse Subscribe for as little as $0 to keep up with everything we're doing. Also, if you can afford to pay a little every month, it really helps us to continue producing great content. We used to think that the human brain was a lot like a computer; using logic to figure out complicated problems. It turns out, it's a lot more complex and, well, weird than that. In this episode of Crash Course Psychology, Hank discusses thinking & communication, solving problems, creating problems, and a few ideas about what our brains are doing up there. -- Table of Contents Thinking & Communicating 01:39:16 Solving Problems 03:21:03 Creating Problems 05:46:06 -- Want to find Crash Course elsewhere on the internet? Facebook - http...

    published: 19 May 2014
developed with YouTube
Intro to Algorithms: Crash Course Computer Science #13
11:44

Intro to Algorithms: Crash Course Computer Science #13

  • Order:
  • Duration: 11:44
  • Updated: 24 May 2017
  • views: 334498
videos
Algorithms are the sets of steps necessary to complete computation - they are at the heart of what our devices actually do. And this isn’t a new concept. Since the development of math itself algorithms have been needed to help us complete tasks more efficiently, but today we’re going to take a look a couple modern computing problems like sorting and graph search, and show how we’ve made them more efficient so you can more easily find cheap airfare or map directions to Winterfell... or like a restaurant or something. Ps. Have you had the chance to play the Grace Hopper game we made in episode 12. Check it out here! http://thoughtcafe.ca/hopper/ CORRECTION: In the pseudocode for selection sort at 3:09, this line: swap array items at index and smallest should be: swap array items at i and smallest Produced in collaboration with PBS Digital Studios: http://youtube.com/pbsdigitalstudios Want to know more about Carrie Anne? https://about.me/carrieannephilbin The Latest from PBS Digital Studios: https://www.youtube.com/playlist?list... Want to find Crash Course elsewhere on the internet? Facebook - https://www.facebook.com/YouTubeCrash... Twitter - http://www.twitter.com/TheCrashCourse Tumblr - http://thecrashcourse.tumblr.com Support Crash Course on Patreon: http://patreon.com/crashcourse CC Kids: http://www.youtube.com/crashcoursekids
https://wn.com/Intro_To_Algorithms_Crash_Course_Computer_Science_13
How To Program For Beginners | Episode 1: Algorithms
24:10

How To Program For Beginners | Episode 1: Algorithms

  • Order:
  • Duration: 24:10
  • Updated: 30 May 2016
  • views: 3225
videos
This is the start to a new series, and I hope to teach you guys all the tricks and tips you need to becoming a successful programmer! If you're interested in more videos, and you want to continue to get better at programming, please subscribe for all future episodes!
https://wn.com/How_To_Program_For_Beginners_|_Episode_1_Algorithms
How Machines Learn
8:55

How Machines Learn

  • Order:
  • Duration: 8:55
  • Updated: 18 Dec 2017
  • views: 2361204
videos
How do all the algorithms around us learn to do their jobs? Bot Wallpapers on Patreon: https://www.patreon.com/posts/15959388 Discuss this video: https://www.reddit.com/r/CGPGrey/comments/7klmd3/how_do_machines_learn/ Footnote: https://www.youtube.com/watch?v=wvWpdrfoEv0 Podcasts: https://www.youtube.com/user/HelloInternetPodcast https://www.youtube.com/channel/UCqoy014xOu7ICwgLWHd9BzQ Thank you to my supporters on Patreon: James Bissonette, James Gill, Cas Eliëns, Jeremy Banks, Thomas J Miller Jr MD, Jaclyn Cauley, David F Watson, Jay Edwards, Tianyu Ge, Michael Cao, Caron Hideg, Andrea Di Biagio, Andrey Chursin, Christopher Anthony, Richard Comish, Stephen W. Carson, JoJo Chehebar, Mark Govea, John Buchan, Donal Botkin, Bob Kunz https://www.patreon.com/cgpgrey How neural networks really work with the real linear algebra: https://www.youtube.com/watch?v=aircAruvnKk Music by: http://www.davidreesmusic.com
https://wn.com/How_Machines_Learn
Python Machine Learning Tutorial | Machine Learning Algorithms | Python Training | Edureka
23:12

Python Machine Learning Tutorial | Machine Learning Algorithms | Python Training | Edureka

  • Order:
  • Duration: 23:12
  • Updated: 07 Apr 2017
  • views: 80842
videos
( Python Training : https://www.edureka.co/python ) This Edureka Python tutorial (Python Tutorial Blog: https://goo.gl/wd28Zr) gives an introduction to Machine Learning and how to implement machine learning algorithms in Python. Below are the topics covered in this tutorial: 1. Why Machine Learning? 2. What is Machine Learning? 3. Types of Machine Learning 4. Supervised Learning 5. KNN algorithm 6. Unsupervised Learning 7. K-means Clustering Algorithm Check out our playlist for more videos: https://goo.gl/Na1p9G Subscribe to our channel to get video updates. Hit the subscribe button above. #Python #PythonTutorial #PythonMachineLearning #PythonTraining How it Works? 1. This is a 5 Week Instructor led Online Course,40 hours of assignment and 20 hours of project work 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will be working on a real time project for which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - - - - About the Course Edureka's Python Online Certification Training will make you an expert in Python programming. It will also help you learn Python the Big data way with integration of Machine learning, Pig, Hive and Web Scraping through beautiful soup. During our Python Certification training, our instructors will help you: 1. Master the Basic and Advanced Concepts of Python 2. Understand Python Scripts on UNIX/Windows, Python Editors and IDEs 3. Master the Concepts of Sequences and File operations 4. Learn how to use and create functions, sorting different elements, Lambda function, error handling techniques and Regular expressions ans using modules in Python 5. Gain expertise in machine learning using Python and build a Real Life Machine Learning application 6. Understand the supervised and unsupervised learning and concepts of Scikit-Learn 7. Master the concepts of MapReduce in Hadoop 8. Learn to write Complex MapReduce programs 9. Understand what is PIG and HIVE, Streaming feature in Hadoop, MapReduce job running with Python 10. Implementing a PIG UDF in Python, Writing a HIVE UDF in Python, Pydoop and/Or MRjob Basics 11. Master the concepts of Web scraping in Python 12. Work on a Real Life Project on Big Data Analytics using Python and gain Hands on Project Experience - - - - - - - - - - - - - - - - - - - Why learn Python? Programmers love Python because of how fast and easy it is to use. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging your programs is a breeze in Python with its built in debugger. Using Python makes Programmers more productive and their programs ultimately better. Python continues to be a favorite option for data scientists who use it for building and using Machine learning applications and other scientific computations. Python runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for the commercial products, because of its OSI-approved open source license. Python has evolved as the most preferred Language for Data Analytics and the increasing search trends on python also indicates that Python is the next "Big Thing" and a must for Professionals in the Data Analytics domain. For more information, please write back to us at sales@edureka.co Call us at US: 1844 230 6362(toll free) or India: +91-90660 20867 Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Customer Review Sairaam Varadarajan, Data Evangelist at Medtronic, Tempe, Arizona: "I took Big Data and Hadoop / Python course and I am planning to take Apache Mahout thus becoming the "customer of Edureka!". Instructors are knowledge... able and interactive in teaching. The sessions are well structured with a proper content in helping us to dive into Big Data / Python. Most of the online courses are free, edureka charges a minimal amount. Its acceptable for their hard-work in tailoring - All new advanced courses and its specific usage in industry. I am confident that, no other website which have tailored the courses like Edureka. It will help for an immediate take-off in Data Science and Hadoop working."
https://wn.com/Python_Machine_Learning_Tutorial_|_Machine_Learning_Algorithms_|_Python_Training_|_Edureka
Why The YouTube Algorithm Will Always Be A Mystery
4:59

Why The YouTube Algorithm Will Always Be A Mystery

  • Order:
  • Duration: 4:59
  • Updated: 15 May 2017
  • views: 747369
videos
The mysterious YouTube algorithm. It's confused people for years, and will continue to do so. So why isn't YouTube more transparent? It used to be that they wouldn't tell anyone how it works - but now, it's that they can't. Let's talk about deep learning algorithms, neural networks, and search engine optimisation. CREDITS: Thanks to animator Matt Ley for the wonderful cartoon of me: https://www.youtube.com/user/Thelaserbearguy I put this together in three days, plus a day of checking and proofing, in Adobe After Effects. It took about eight hours to render, but that's because every frame has keying, lighting, camera, and motion blur effects, and because the original footage of me was in 4.6k lossless. Yes, the sound of the black box working is the sound of a microwave (it's the one in my kitchen). Also, those aren't faked desktop screenshots, I had to install a copy of Windows ME to make this. SOURCES: "Deep Neural Networks for YouTube Recommendations", https://research.google.com/pubs/archive/45530.pdf [PDF] — some people are saying this link 404s, but it works for me? Search for the title and you'll find it. There's a good layperson summary of the paper here: http://www.tubefilter.com/2017/02/16/youtube-algorithm-reverse-engineering-part-ii/ The Defamation Act is published under the Open Government License 3.0: http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/ and is available at http://www.legislation.gov.uk/ukpga/2013/26/contents/enacted The music in the cartoon section is called 'Ukulele Beach', and it's in the YouTube audio library. REFERENCES: There are a lot of references and in-jokes in here, and hopefully people will spot most of them in the comments. But if anyone wants confirmation: yes, there are references to Billy Joel, Aqua, a He-Man remix, and Elton John. The last one's pretty obscure, well done to you at home if you got that. VFX breakdown and references explained: https://www.youtube.com/watch?v=6s9aGt2Lkgw ABOUT ME: I'm at http://tomscott.com on Twitter at http://twitter.com/tomscott on Facebook at http://facebook.com/tomscott and on Snapchat and Instagram as tomscottgo
https://wn.com/Why_The_Youtube_Algorithm_Will_Always_Be_A_Mystery
Brian Christian & Tom Griffiths: "Algorithms to Live By" | Talks at Google
1:07:28

Brian Christian & Tom Griffiths: "Algorithms to Live By" | Talks at Google

  • Order:
  • Duration: 1:07:28
  • Updated: 12 May 2016
  • views: 71709
videos
Practical, everyday advice which will easily provoke an interest in computer science. In a dazzlingly interdisciplinary work, acclaimed author Brian Christian and cognitive scientist Tom Griffiths show how the algorithms used by computers can also untangle very human questions. They explain how to have better hunches and when to leave things to chance, how to deal with overwhelming choices and how best to connect with others. From finding a spouse to finding a parking spot, from organizing one's inbox to understanding the workings of memory, Algorithms to Live By transforms the wisdom of computer science into strategies for human living. Brian Christian is the author of The Most Human Human, a Wall Street Journal bestseller, New York Times editors’ choice, and a New Yorker favorite book of the year. His writing has appeared in The New Yorker, The Atlantic, Wired, The Wall Street Journal, The Guardian, and The Paris Review, as well as in scientific journals such as Cognitive Science, and has been translated into eleven languages. He lives in San Francisco. Tom Griffiths is a professor of psychology and cognitive science at UC Berkeley, where he directs the Computational Cognitive Science Lab. He has published more than 150 scientific papers on topics ranging from cognitive psychology to cultural evolution, and has received awards from the National Science Foundation, the Sloan Foundation, the American Psychological Association, and the Psychonomic Society, among others. He lives in Berkeley. On behalf of Talks at Google this talk was hosted by Boris Debic. eBook https://play.google.com/store/books/details/Brian_Christian_Algorithms_to_Live_By?id=yvaLCgAAQBAJ
https://wn.com/Brian_Christian_Tom_Griffiths_Algorithms_To_Live_By_|_Talks_At_Google
Algorithm using Flowchart and Pseudo code Level 1 Flowchart
5:41

Algorithm using Flowchart and Pseudo code Level 1 Flowchart

  • Order:
  • Duration: 5:41
  • Updated: 27 Aug 2013
  • views: 451971
videos
Algorithm using Flowchart and Pseudo code Level 1 Flowchart By: Yusuf Shakeel http://www.dyclassroom.com/flowchart/introduction 0:05 Things we will learn 0:21 Level 0:28 Level 1 Flowchart 0:33 Important terms 0:37 Procedure 0:45 Algorithm 0:54 Flowchart 1:00 Pseudo code 1:08 Answer this simple question 1:14 How will you log into your facebook account 1:30 Next question 1:32 Write an algorithm to log into your facebook account 1:44 Algorithm to log in to facebook account in simple English 2:06 Writing Algorithm 2:14 Flowchart 2:16 There are 6 basic symbols that are commonly used in Flowchart 2:20 Terminal 2:27 Input/Output 2:35 Process 2:42 Decision 2:52 Connector 3:00 Control Flow 3:06 All the 6 symbols 3:13 Flowchart rules 3:25 Flowchart exercise 3:28 Add 10 and 20 4:00 Another exercise 4:03 Find the sum of 5 numbers 4:34 Another exercise 4:35 Print Hello World 10 times 5:06 Another exercise 5:07 Draw a flowchart to log in to facebook account 5:26 Note! End of Level 1 Related Videos Algorithm Flowchart and Pseudo code Level 1 Flowchart http://youtu.be/vOEN65nm4YU Level 2 Important Programming Concepts http://youtu.be/kwA3M8YxNk4 Level 3 Pseudo code http://youtu.be/r1BpraNa2Zc
https://wn.com/Algorithm_Using_Flowchart_And_Pseudo_Code_Level_1_Flowchart
CppCon 2017: Nicholas Ormrod “Fantastic Algorithms and Where To Find Them”
46:58

CppCon 2017: Nicholas Ormrod “Fantastic Algorithms and Where To Find Them”

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  • Duration: 46:58
  • Updated: 27 Oct 2017
  • views: 13680
videos
Presentation Slides, PDFs, Source Code and other presenter materials are available at: https://github.com/CppCon/CppCon2017 — Come dive into some exciting algorithms — tools rare enough to be novel, but useful enough to be found in practice. Want to learn about "heavy hitters" to prevent DOS attacks? Come to this talk. Want to avoid smashing your stack during tree destruction? Come to this talk. Want to hear war stories about how a new algorithm saved the day? Come to this talk! We'll dive into the finest of algorithms and see them in use — Fantastic Algorithms, and Where To Find Them. — Nicholas Ormrod: Facebook, Software Engineer Nicholas is a infrastructure engineer at Facebook. If he talks too much, disable him with a well-placed nerd snipe. — Videos Filmed & Edited by Bash Films: http://www.BashFilms.com
https://wn.com/Cppcon_2017_Nicholas_Ormrod_“Fantastic_Algorithms_And_Where_To_Find_Them”
Ensemble learners
2:52

Ensemble learners

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  • Duration: 2:52
  • Updated: 06 Jun 2016
  • views: 26169
videos
This video is part of the Udacity course "Machine Learning for Trading". Watch the full course at https://www.udacity.com/course/ud501
https://wn.com/Ensemble_Learners
Algorithms and Tips You Need to know to Master EPLL
4:12

Algorithms and Tips You Need to know to Master EPLL

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  • Duration: 4:12
  • Updated: 06 Apr 2017
  • views: 3322
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Hope this video helped! Thanks for watching! Video idea I may or may not continue: Basically, you guys can film yourselves on any event official or unofficial, and you can send in a good solve for YOUR standards. Note: Good reactions will be targeted Then, each month maybe, or 2 months, I'll upload a 'best solves of the month'. Featuring your videos. What defines best? Just an interesting solve of yours, maybe an event your good at, maybe an official solve, and good reactions will be fun to watch. How to send in videos: Nothing fancy, just upload to youtube public or unlisted and private message me a link to it. Or if you really want, you can just send the link here in the comments. Now remember, I'm not sure I will continue this series, I just want to see how successful and entertaining it is. Also, my PBs! (Let me know if you can't access them) https://docs.google.com/spreadsheets/d/1-_G72PqdH3o4V3UpeWQLaoPLd6M5G_BxlY7iB03-rg8/edit#gid=0
https://wn.com/Algorithms_And_Tips_You_Need_To_Know_To_Master_Epll
Sorting in Python  ||  Learn Python Programming  (Computer Science)
6:24

Sorting in Python || Learn Python Programming (Computer Science)

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  • Duration: 6:24
  • Updated: 08 Oct 2017
  • views: 26407
videos
Sorting is a fundamental task in software engineering. In Python, there are a variety of ways to sort lists, tuples, and other objects. Today we talk about the sort() method which is an in-place algorithm for sorting lists. We also cover the sorted() function which can be used on more objects, and creates a sorted copy, leaving the original object unchanged. We were able to make this Python video with the help of our Patrons on Patreon! We would like to recognize the generosity of our VIP Patrons Matt Peters, Andrew Mengede, Martin Stephens, and Markie Ward. Thank you so much for helping us continue our work! ➢➢➢➢➢➢➢➢➢➢ To​ ​help​ us continue making videos,​ ​you​ ​can​ ​support​ Socratica at: ​Patreon​: https://www.patreon.com/socratica Socratica Paypal: https://www.paypal.me/socratica We also accept Bitcoin! :) Our​ ​address​ ​is: 1EttYyGwJmpy9bLY2UcmEqMJuBfaZ1HdG9 Thank​ ​you!! ➢➢➢➢➢➢➢➢➢➢ If you’d like a reference book, we recommend “Python Cookbook, 3rd Edition” from O’Reilly: http://amzn.to/2sCNYlZ The Mythical Man Month - Essays on Software Engineering & Project Management http://amzn.to/2tYdNeP ➢➢➢➢➢➢➢➢➢➢ You​ ​can​ ​also​ ​follow​ ​Socratica​ ​on: -​ ​Twitter:​ ​@socratica -​ ​Instagram:​ ​@SocraticaStudios -​ ​Facebook:​ ​@SocraticaStudios ➢➢➢➢➢➢➢➢➢➢ Python instructor: Ulka Simone Mohanty (@ulkam on Twitter) Written & Produced by Michael Harrison (@mlh496 on Twitter)
https://wn.com/Sorting_In_Python_||_Learn_Python_Programming_(Computer_Science)
Computational Thinking: Algorithm Design
14:06

Computational Thinking: Algorithm Design

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  • Duration: 14:06
  • Updated: 02 Mar 2016
  • views: 7329
videos
This video introduces the concept of Algorithm Design in Computational Thinking. It is part of a short course to introduce Middle and High School teachers to Computational Thinking. Learn more at http://www.curriki.org/oer/Algorithm-Design-101423/?mrid=101147
https://wn.com/Computational_Thinking_Algorithm_Design
Algorithms: Graph Search, DFS and BFS
11:49

Algorithms: Graph Search, DFS and BFS

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  • Duration: 11:49
  • Updated: 27 Sep 2016
  • views: 211147
videos
Learn the basics of graph search and common operations; Depth First Search (DFS) and Breadth First Search (BFS). This video is a part of HackerRank's Cracking The Coding Interview Tutorial with Gayle Laakmann McDowell. http://www.hackerrank.com/domains/tutorials/cracking-the-coding-interview?utm_source=video&utm_medium=youtube&utm_campaign=ctci
https://wn.com/Algorithms_Graph_Search,_Dfs_And_Bfs
How to Figure Out the Day of the Week For Any Date Ever
7:53

How to Figure Out the Day of the Week For Any Date Ever

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  • Duration: 7:53
  • Updated: 16 Jan 2018
  • views: 362827
videos
To learn more about Brilliant, go to https://brilliant.org/BeSmart/ and sign up for free. First 200 people will get 20% off the annual Premium subscription. ↓↓↓ More info and sources below ↓↓↓ You can be a human computer too. Our cheat sheet: http://bit.ly/2rftqkv Want to go NEXT LEVEL? Learn how to adjust for Julian calendar and BC dates You might think that computers are the only things that run algorithms, but you’re wrong. Here’s a neat mental trick for calculating the day of the week for any day ever, developed by famous mathematician John H. Conway Don’t miss our next video! SUBSCRIBE! ►► http://bit.ly/iotbs_sub READ MORE: https://en.wikipedia.org/wiki/Doomsday_rule Martin Gardner, "The Universe in a Handkerchief: Lewis Carroll's Mathematical Recreations, Games, Puzzles, and Word Plays" ----------- FOLLOW US: Merch: https://store.dftba.com/collections/its-okay-to-be-smart Facebook: http://www.facebook.com/itsokaytobesmart Twitter:@DrJoeHanson @okaytobesmart Tumblr: http://www.itsokaytobesmart.com Instagram: @DrJoeHanson ----------- It’s Okay To Be Smart is hosted by Joe Hanson, Ph.D. Director: Joe Nicolosi Writer: Joe Hanson, Ph.D. Producer/editor/animator: Jordan Husmann Producer: Stephanie Noone and Amanda Fox Produced by PBS Digital Studios Music via APM Stock images from Shutterstock http://www.shutterstock.com ------
https://wn.com/How_To_Figure_Out_The_Day_Of_The_Week_For_Any_Date_Ever
Predicting Stock Price Mathematically
11:33

Predicting Stock Price Mathematically

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  • Duration: 11:33
  • Updated: 07 Nov 2015
  • views: 106302
videos
There are two prices that are critical for any investor to know: the current price of the investment he or she owns, or plans to own, and its future selling price. Despite this, investors are constantly reviewing past pricing history and using it to influence their future investment decisions. Some investors won't buy a stock or index that has risen too sharply, because they assume that it's due for a correction, while other investors avoid a falling stock, because they fear that it will continue to deteriorate. http://www.garguniversity.com Check out Ebook "Mind Math" from Dr. Garg https://www.amazon.com/MIND-MATH-Learn-Math-Fun-ebook/dp/B017QEIF18
https://wn.com/Predicting_Stock_Price_Mathematically
YouTube Algorithm 2017 Explained - The A.I. Behind The Curtain
33:07

YouTube Algorithm 2017 Explained - The A.I. Behind The Curtain

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  • Duration: 33:07
  • Updated: 09 Aug 2017
  • views: 28400
videos
Here is part of my CVXLive 2017 Presentation: YouTube Algorithm 2017 Explained - The A.I. Behind The Curtain. This is the 3rd part of the Decoding the YouTube Algorithm and learn how to grow fast on YouTube with Algorithm Driven views series. Learn about YouTube Machine Learning Technology and how it interacts with viewers, videos, and channels. Get Access to Free VidSummit Replays https://vidsummit.com/freereplays Tickets to VidSummit 2017 https://vidsummit.com Decoding the YouTube Algorithm and learn how to grow fast on YouTube with Algorithm Driven views series ➜ https://goo.gl/sa6aGp Get More Great Tips - Subscribe ➜ http://goo.gl/dWNo9H Share this Video: ➜ https://youtu.be/Ix1gnDmuMyI My Favorite YouTube Tool TubeBuddy Download TubeBuddy Free Today! ➜ http://derral.link/tubebuddy Join My Patreon Community for More Advanced Training Check Out Our Community! ➜ http://derral.link/patreon ★ ★ Be the Next Lucky Subscriber to get an In-depth Channel Evaluation: 1. Must be subscribed to My YouTube Channel Subscribe ➜ http://goo.gl/dWNo9H 2. Must be one of my Patrons on Patreon. Check it out! ➜ http://derral.link/patreon 3. Must be uploading good quality content frequently to your YouTube Channel and really trying hard to make it 4. Must be engaged in my channel by liking, commenting, posting, sharing and encouraging others to subscribe to my channel. Ask me A Question by using hashtag on YouTube or Twitter #AskDerral @derraleves
https://wn.com/Youtube_Algorithm_2017_Explained_The_A.I._Behind_The_Curtain
12. Clustering
50:40

12. Clustering

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  • Duration: 50:40
  • Updated: 19 May 2017
  • views: 35539
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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
https://wn.com/12._Clustering
Ethereum Games Explained
9:03

Ethereum Games Explained

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  • Duration: 9:03
  • Updated: 13 Apr 2018
  • views: 6853
videos
Crypto-kitties! I'm going to cover the most important parts of the popular crypto-kitties game built on the Ethereum blockchain in this video. The game is over 2000 lines of Solidity code and it allows players to buy, sell, and breed these collectible cats. At one point, this game accounted for a third of transactions on the Ethereum network which is absolutely insane. This is a great example of a wildly popular use case for a decentralized application. There is a lot of potential here to make a game that people obsess over and makes both the creators and players a good amount of money. Enjoy! Code for this video: https://github.com/llSourcell/Cryptokitties 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 More learning resources: https://news.elearninginside.com/forget-cryptokitties-cryptozombies-will-teach-everything-need-know-creating-ethereum-game/ https://www.cryptokitties.co/ https://motherboard.vice.com/en_us/article/a3y4k5/after-cryptokitties-the-cryptocollectibles-business-is-booming-cryptobots https://github.com/cryptocopycats/awesome-cryptokitties https://ethereum-virtual-machine.quora.com/I-Bred-Crypto-Kitties-on-the-Ethereum-Blockchain 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
https://wn.com/Ethereum_Games_Explained
Gradient descent, how neural networks learn | Chapter 2, deep learning
21:01

Gradient descent, how neural networks learn | Chapter 2, deep learning

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  • Duration: 21:01
  • Updated: 16 Oct 2017
  • views: 632328
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Subscribe for more (part 3 will be on backpropagation): http://3b1b.co/subscribe Thanks to everybody supporting on Patreon. https://www.patreon.com/3blue1brown http://3b1b.co/nn2-thanks For any early stage ML startup founders, Amplify Partners would love to hear from you via 3blue1brown@amplifypartners.com To learn more, I highly recommend the book by Michael Nielsen http://neuralnetworksanddeeplearning.com/ The book walks through the code behind the example in these videos, which you can find here: https://github.com/mnielsen/neural-networks-and-deep-learning MNIST database: http://yann.lecun.com/exdb/mnist/ Also check out Chris Olah's blog: http://colah.github.io/ His post on Neural networks and topology is particular beautiful, but honestly all of the stuff there is great. And if you like that, you'll *love* the publications at distill: https://distill.pub/ For more videos, Welch Labs also has some great series on machine learning: https://youtu.be/i8D90DkCLhI https://youtu.be/bxe2T-V8XRs "But I've already voraciously consumed Nielsen's, Olah's and Welch's works", I hear you say. Well well, look at you then. That being the case, I might recommend that you continue on with the book "Deep Learning" by Goodfellow, Bengio, and Courville. Thanks to Lisha Li (@lishali88) for her contributions at the end, and for letting me pick her brain so much about the material. Here are the articles she referenced at the end: https://arxiv.org/abs/1611.03530 https://arxiv.org/abs/1706.05394 https://arxiv.org/abs/1412.0233 Music by Vincent Rubinetti: https://soundcloud.com/vincerubinetti/ ------------------ 3blue1brown is a channel about animating math, in all senses of the word animate. And you know the drill with YouTube, if you want to stay posted on new videos, subscribe, and click the bell to receive notifications (if you're into that). If you are new to this channel and want to see more, a good place to start is this playlist: http://3b1b.co/recommended Various social media stuffs: Website: https://www.3blue1brown.com Twitter: https://twitter.com/3Blue1Brown Patreon: https://patreon.com/3blue1brown Facebook: https://www.facebook.com/3blue1brown Reddit: https://www.reddit.com/r/3Blue1Brown
https://wn.com/Gradient_Descent,_How_Neural_Networks_Learn_|_Chapter_2,_Deep_Learning
'The Algorithm' - How YouTube Search & Discovery Works
2:02

'The Algorithm' - How YouTube Search & Discovery Works

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  • Duration: 2:02
  • Updated: 28 Aug 2017
  • views: 295001
videos
Welcome to this series of videos on how YouTube's search & discovery system works. In this first installment, we talk about how our 'algorithm' follows the audience. WATCH THE NEXT VIDEO: https://goo.gl/SJiwDS GO TO THE LESSON: https://goo.gl/qV5PgY SUBSCRIBE: https://goo.gl/So4XIG With over 400 hours of video uploaded every minute, that can be a challenge. YouTube’s recommendation systems provide a real-time feedback loop to cater to each viewer and their varying interests. It learns from over 80 billion bits of feedback from the audience, daily, to understand how to serve the right videos to the right viewers at the right time. Our goal is to get people to watch more videos that they enjoy, so that they come back to YouTube regularly. Creators often ask, “What kind of videos does the algorithm like most?” Our systems have no opinion about what type of video you make, and doesn’t favor any particular format. Rather, it tries its best to follow the audience by paying attention to things like: • what they watch • what they don’t watch • how much time they spend watching • likes and dislikes • ‘not interested’ feedback Instead of worrying about what the algorithm likes, it’s better to focus on what your audience likes instead. If you do that and people watch, the algorithm will follow. So, which videos do they enjoy most? How often do they like to watch your channel? Check your YouTube Analytics to answer these questions. Whether you’re pursuing a passion or a business, we strive to give every video a chance to reach its potential audience. We realize however that YouTube has a lot of features, and it can be easy to get confused. Keep watching to learn about six key places where your videos appear, and what you can do to improve your chances for success: Search, Suggested Videos, Home, Trending, Subscriptions, and Notifications, in no particular order. - Level up your YouTube skills with Creator Academy lessons: http://goo.gl/E9umlU - See index of all lessons: http://goo.gl/x2h1NG - Get how-to step-by-step help: http://goo.gl/fBzr7
https://wn.com/'The_Algorithm'_How_Youtube_Search_Discovery_Works
But what *is* a Neural Network? | Chapter 1, deep learning
19:13

But what *is* a Neural Network? | Chapter 1, deep learning

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  • Duration: 19:13
  • Updated: 05 Oct 2017
  • views: 1426628
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Subscribe to stay notified about new videos: http://3b1b.co/subscribe Support more videos like this on Patreon: https://www.patreon.com/3blue1brown Special thanks to these supporters: http://3b1b.co/nn1-thanks For any early-stage ML entrepreneurs, Amplify Partners would love to hear from you: 3blue1brown@amplifypartners.com Full playlist: http://3b1b.co/neural-networks Typo correction: At 14:45, the last index on the bias vector is n, when it's supposed to in fact be a k. Thanks for the sharp eyes that caught that! For those who want to learn more, I highly recommend the book by Michael Nielsen introducing neural networks and deep learning: https://goo.gl/Zmczdy There are two neat things about this book. First, it's available for free, so consider joining me in making a donation Nielsen's way if you get something out of it. And second, it's centered around walking through some code and data which you can download yourself, and which covers the same example that I introduce in this video. Yay for active learning! https://github.com/mnielsen/neural-networks-and-deep-learning I also highly recommend Chris Olah's blog: http://colah.github.io/ For more videos, Welch Labs also has some great series on machine learning: https://youtu.be/i8D90DkCLhI https://youtu.be/bxe2T-V8XRs For those of you looking to go *even* deeper, check out the text "Deep Learning" by Goodfellow, Bengio, and Courville. Also, the publication Distill is just utterly beautiful: https://distill.pub/ Lion photo by Kevin Pluck Music by Vincent Rubinetti: https://soundcloud.com/vincerubinetti/ ------------------ 3blue1brown is a channel about animating math, in all senses of the word animate. And you know the drill with YouTube, if you want to stay posted on new videos, subscribe, and click the bell to receive notifications (if you're into that). If you are new to this channel and want to see more, a good place to start is this playlist: http://3b1b.co/recommended Various social media stuffs: Website: https://www.3blue1brown.com Twitter: https://twitter.com/3Blue1Brown Patreon: https://patreon.com/3blue1brown Facebook: https://www.facebook.com/3blue1brown Reddit: https://www.reddit.com/r/3Blue1Brown
https://wn.com/But_What_Is_A_Neural_Network_|_Chapter_1,_Deep_Learning
2018 Website Trends: AI Algorithms
1:01

2018 Website Trends: AI Algorithms

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  • Duration: 1:01
  • Updated: 22 Jan 2018
  • views: 15
videos
In terms of the web and the evolution of it, content has become much more focused on you as an individual. Currently, he sites you go to for news show a dashboard that is most pertinent to you and your social feeds are catered and customized exactly for you. In 2018, websites in general are going to begin to do more of this. In order to make content more personal, machine learning and artificial intelligence algorithms will be relied on more often. This will create a more personal experience, serving up the most engaging and appropriate content for each user. This will really come into the limelight throughout 2018. And, it will continue to advance in 2019 and the years that follow. For more 2018 website trends, visit: https://www.yokoco.com/2018/01/16/2018-website-trends/ In this video is Chris Yoko, President of Yoko Co - which is an interactive marketing firm that works with organizations of all sizes to develop and execute integrated marketing initiatives. To learn more about us, visit: https://www.yokoco.com/
https://wn.com/2018_Website_Trends_Ai_Algorithms
What Are Algorithms in Data Analytics - Data Science Jargon for Beginners
2:10

What Are Algorithms in Data Analytics - Data Science Jargon for Beginners

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  • Duration: 2:10
  • Updated: 23 Nov 2017
  • views: 124
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In this video i am going to explain what algorithms are in data analytics and how data analysts and data scientists use algorithms to extract data from big data databases. ► Full Playlist Explaining Data Jargon ( https://www.youtube.com/playlist?list=PL_9qmWdi19yDhnzqVCAhA4ALqDoqjeUOr ) ► http://jobsinthefuture.com/index.php/2017/11/23/what-are-algorithms-in-data-analytics-data-science-jargon-for-beginners/ Trying to make sense of the big data industry? Make sure you know your terms if you want to keep your head above water earn a data career. There is a lot of technical jargon floating around the data science industry and over the past week I have been defining some of these key terms to help you make better sense as you develop your interest and understanding of the industry. What are Algorithms. When you are researching Data Analytics, Business Analytics, or Data Science you will hear a lot about Algorithms. Algorithms: A set of rules for solving a problem in a finite number of steps in order to find the greatest common divisor. Algorithms are the way in which a data analyst takes millions and millions of little bits of data, processes them through data analytics tools like Hadoop, Tableau, or Apache Spark and come out on the other side with a common divisor. Common Divisor: In the data industry this is what analysts are search for. What is trending, who is buying what, where are they going, etc... For example: The common divisor is what companies want to know so that they know where to market their products for the great return on investment. Confused about Data Analyst Vs. Data Scientist? Check out the Article that defines the differences and clarify what is best for you! ►https://www.youtube.com/watch?v=_Vi9W_2cxYA&t=2s&list=PL_9qmWdi19yDhnzqVCAhA4ALqDoqjeUOr&index=1 ------- SOCIAL Twitter ► @jobsinthefuture Facebook ►/jobsinthefuture Instagram ►@Jobsinthefuture WHERE I LEARN: (affiliate links) Lynda.com ► http://bit.ly/2rQB2u4 edX.org ► http://fxo.co/4y00 MY FAVORITE GEAR: (affiliate links) Camera ► http://amzn.to/2BWvE9o CamStand ► http://amzn.to/2BWsv9M Compute ► http://amzn.to/2zPeLvs Mouse ► http://amzn.to/2C0T9hq TubeBuddy ► https://www.tubebuddy.com/bengkaiser ► Download the Ultimate Guide Now! ( https://www.getdrip.com/forms/883303253/submissions/new ) Thanks for Supporting Our Channel! DISCLAIMER: This video and description contains affiliate links, which means that if you click on one of the product links, I’ll receive a small commission. This help support the channel and allows us to continue to make videos like this. Thank you for the support!
https://wn.com/What_Are_Algorithms_In_Data_Analytics_Data_Science_Jargon_For_Beginners
Cognition: How Your Mind Can Amaze and Betray You - Crash Course Psychology #15
10:42

Cognition: How Your Mind Can Amaze and Betray You - Crash Course Psychology #15

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  • Duration: 10:42
  • Updated: 19 May 2014
  • views: 1425009
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You can directly support Crash Course at http://www.subbable.com/crashcourse Subscribe for as little as $0 to keep up with everything we're doing. Also, if you can afford to pay a little every month, it really helps us to continue producing great content. We used to think that the human brain was a lot like a computer; using logic to figure out complicated problems. It turns out, it's a lot more complex and, well, weird than that. In this episode of Crash Course Psychology, Hank discusses thinking & communication, solving problems, creating problems, and a few ideas about what our brains are doing up there. -- Table of Contents Thinking & Communicating 01:39:16 Solving Problems 03:21:03 Creating Problems 05:46:06 -- Want to find Crash Course elsewhere on the internet? Facebook - http://www.facebook.com/YouTubeCrashCourse Twitter - http://www.twitter.com/TheCrashCourse Tumblr - http://thecrashcourse.tumblr.com Support CrashCourse on Subbable: http://subbable.com/crashcourse
https://wn.com/Cognition_How_Your_Mind_Can_Amaze_And_Betray_You_Crash_Course_Psychology_15