EPISODE · Feb 3, 2017 · 9 MIN
How to Do Mathematics Easily - Intro to Deep Learning #4
from Siraj Raval
Let's learn about some key math concepts behind deep learning shall we? We'll build a 3 layer neural network and dive into some key concepts that makes deep learning give us such incredible results. Coding challenge for this video: https://github.com/llSourcell/how_to_do_math_for_deep_learning Jovian's Winning Code: https://github.com/jovianlin/siraj-intro-to-DL-03/blob/master/Siraj%2003%20Challenge.ipynb Vishal's Runner up Code: https://github.com/erilyth/DeepLearning-SirajologyChallenges/tree/master/Sentiment_Analysis Linear Algebra cheatsheet: http://www.souravsengupta.com/cds2016/lectures/Savov_Notes.pdf Calculus cheatsheet: http://tutorial.math.lamar.edu/pdf/Calculus_Cheat_Sheet_All.pdf Statistics cheatsheet: http://web.mit.edu/~csvoss/Public/usabo/stats_handout.pdf And if you have never had experience with any of these 3 and want to learn from absolute scratch, I'd recommend the respective KhanAcademy courses: https://www.khanacademy.org/math More Learning Resources: https://people.ucsc.edu/~praman1/static/pub/math-for-ml.pdf http://www.vision.jhu.edu/tutorials/ICCV15-Tutorial-Math-Deep-Learning-Intro-Rene-Joan.pdf http://datascience.ibm.com/blog/the-mathematics-of-machine-learning/ Join us in our Slack channel: http://wizards.herokuapp.com/ And Part I of this book is so dope, seriously: http://www.deeplearningbook.org/ Please subscribe! And like. And comment. That's what keeps me going. And please support me on Patreon: https://www.patreon.com/user?u=3191693 Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/
What this episode covers
Let's learn about some key math concepts behind deep learning shall we? We'll build a 3 layer neural network and dive into some key concepts that makes deep learning give us such incredible results. Coding challenge for this video: https://github.com/llSourcell/how_to_do_math_for_deep_learning Jovian's Winning Code: https://github.com/jovianlin/siraj-intro-to-DL-03/blob/master/Siraj%2003%20Challenge.ipynb Vishal's Runner up Code: https://github.com/erilyth/DeepLearning-SirajologyChallenges/tree/master/Sentiment_Analysis Linear Algebra cheatsheet: http://www.souravsengupta.com/cds2016/lectures/Savov_Notes.pdf Calculus cheatsheet: http://tutorial.math.lamar.edu/pdf/Calculus_Cheat_Sheet_All.pdf Statistics cheatsheet: http://web.mit.edu/~csvoss/Public/usabo/stats_handout.pdf And if you have never had experience with any of these 3 and want to learn from absolute scratch, I'd recommend the respective KhanAcademy courses: https://www.khanacademy.org/math More Learning Resources: https://people.ucsc.edu/~praman1/static/pub/math-for-ml.pdf http://www.vision.jhu.edu/tutorials/ICCV15-Tutorial-Math-Deep-Learning-Intro-Rene-Joan.pdf http://datascience.ibm.com/blog/the-mathematics-of-machine-learning/ Join us in our Slack channel: http://wizards.herokuapp.com/ And Part I of this book is so dope, seriously: http://www.deeplearningbook.org/ Please subscribe! And like. And comment. That's what keeps me going. And please support me on Patreon: https://www.patreon.com/user?u=3191693 Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/
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How to Do Mathematics Easily - Intro to Deep Learning #4
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