My summary of all yotube videos of siraj and the deep learning course at Udacity on my way to learn Machine Learning
Feel free to share, fork and pull this file. :-)
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How to Make a Prediction - Intro to Deep Learning #1 D: 7:52
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How to Make a Neural Network - Intro to Deep Learning #2 D: 9:20
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How to Do Sentiment Analysis - Intro to Deep Learning #3 D: 9:21 min.
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How to Make Word Vectors from Game of Thrones (LIVE) 49:25
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How to Do Mathematics Easily - Intro to Deep Learning #4 9:51
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How to Predict Music You Love (LIVE) 51:31
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How to Make Data Amazing - Intro to Deep Learning #5 8:44
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How to Simplify Your Dataset Easily (LIVE) 1:00:16
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How to Make an Image Classifier - Intro to Deep Learning #6 8:45
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How to Make a Tensorflow Image Classifier (LIVE) 52:15
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How to Predict Stock Prices Easily - Intro to Deep Learning #7 9:58
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How to Use Tensorflow for Time Series (Live) 1:06:31
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How to Generate Art - Intro to Deep Learning #8 8:57
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How to Do Style Transfer with Tensorflow (LIVE) 1:06:26
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How to Generate Music - Intro to Deep Learning #9 8:22
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How to Generate Music with Tensorflow (LIVE) 1:03:10
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How to Make a Text Summarizer - Intro to Deep Learning #10 9:06
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How to Generate Your Own Wikipedia Articles (LIVE) 1:11:44
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How to Make a Language Translator - Intro to Deep Learning #11 8:48
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How to Use Tensorflow for Seq2seq Models (LIVE) 58:36
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How to Make a Chatbot - Intro to Deep Learning #12 8:34
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How to Use Tensorboard (LIVE) 56:04
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How to Win Slot Machines - Intro to Deep Learning #13 9:39
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How to Beat Pong Using Policy Gradients (LIVE) 1:10:27
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How to Generate Images - Intro to Deep Learning #14 8:48
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How to Generate Images with Tensorflow (LIVE) 1:02:51
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How to Generate Video - Intro to Deep Learning #15 9:41
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Generative Adversarial Networks (LIVE) 1:04:41
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How to Convert Text to Images - Intro to Deep Learning #16 9:33
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Generative Adversarial Networks for Style Transfer (LIVE) 1:03:42
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How to Learn from Little Data - Intro to Deep Learning #17 8:53
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Differentiable Neural Computer (LIVE) 1:03:56
Welcome to Intro to Deep Learning! This course is for anyone who wants to become a deep learning engineer. I'll take you from the very basics of deep learning to the bleeding edge over the course of 4 months. In this video, we’ll predict an animal’s body weight given it’s brain weight using linear regression via 10 lines of Python. I’ll have a live session every Wednesday at 10 AM PST that covers my weekly video topics in depth. You can click on the little notification bell next to the subscribe button to get an email notification whenever I’m live. And each session is recorded and uploaded to this channel in case you miss it. This Youtube content is 100% created by me (from the writing to the editing, etc.) , it’ll all be released on my channel, and it’s totally free.
I am also very proud and excited to announce my new, exclusive partnership with Udacity. Together, we’re offering the new Deep Learning Nanodegree Foundation program. If you want to take your game to the next level, this is for you! Especially since Udacity will be providing guaranteed admission to their groundbreaking Artificial Intelligence and Self-Driving Car Nanodegree programs to all graduates. They’re offering discounted limited-time pricing, so enroll now to enjoy the unique projects, program sets, and expert reviews. Plus, their community is amazing, so don’t forget to join the Slack channel after you enroll (I’ll be in there too!) And hey, I’m getting paid a small royalty from each enrollment, so let’s do this together!
The point of this is to demonstrate the concept of gradient descent. Gradient descent is the most popular optimization strategy in deep learning, in particular an implementation of it called backpropagation. We are using gradient descent as our optimization strategy for linear regression. We'll draw the line of best fit to measure the relationship between student test scores and the amount of hours studied.
How do we learn? In this video, I'll discuss our brain's biological neural network, then we'll talk about how an artificial neural network works. We'll create our own single layer feedforward network in Python, demo it, and analyze the implications of our results. This is the 2nd weekly video in my intro to deep learning series (Udacity nanodegree)
In this video, we'll use machine learning to help classify emotions! The example we'll use is classifying a movie review as either positive or negative via TF Learn in 20 lines of Python.
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.