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Data Science: Deep Learning in Python
Welcome
Introduction and Outline (6:32)
Special Offer! Get the VIP version of this course (1:14)
Where to get the code (5:01)
How to succeed in this course (5:51)
Preliminaries: From Neurons to Neural Networks
Neural Networks with No Math (4:20)
Where does this course fit into your deep learning studies? (4:57)
Deep Learning Readiness Test (5:33)
Introduction to the E-Commerce Course Project (8:53)
Classifying more than 2 things at a time
Prediction: Section Introduction and Outline (5:39)
From Logistic Regression to Neural Networks (5:12)
Softmax (2:54)
Sigmoid vs. Softmax (1:30)
Where to get the code for this course (1:30)
Feedforward in Slow-Mo (part 1) (19:42)
Feedforward in Slow-Mo (part 2) (10:55)
Softmax in Code (3:39)
Building an entire feedforward neural network in Python (6:23)
E-Commerce Course Project: Pre-Processing the Data (5:24)
E-Commerce Course Project: Making Predictions (3:55)
Prediction Quizzes (3:25)
Prediction: Section Summary (1:45)
Training a neural network
Training: Section Introduction and Outline (2:50)
What do all these symbols and letters mean? (9:45)
What does it mean to "train" a neural network? (6:15)
Backpropagation Intro (11:53)
Backpropagation - what does the weight update depend on? (4:47)
Backpropagation - recursiveness (4:37)
Backpropagation in Code (17:07)
The WRONG Way to Learn Backpropagation (3:52)
E-Commerce Course Project: Training Logistic Regression with Softmax (8:11)
E-Commerce Course Project: Training a Neural Network (6:19)
Training Quizzes (5:31)
Training: Section Summary (2:41)
Practical Machine Learning
Practical Issues: Section Introduction and Outline (1:43)
Donut and XOR Review (1:06)
Donut and XOR Revisited (4:21)
Common nonlinearities and their derivatives (1:26)
Hyperparameters and Cross-Validation (4:11)
Manually Choosing Learning Rate and Regularization Penalty (4:08)
Practical Issues: Section Summary (6:10)
TensorFlow, exercises, practice, and what to learn next
TensorFlow plug-and-play example (7:32)
Visualizing what a neural network has learned using TensorFlow Playground (11:35)
Where to go from here (3:41)
You know more than you think you know (4:52)
How to get good at deep learning + exercises (5:07)
Deep neural networks in just 3 lines of code with Sci-Kit Learn (8:49)
Project: Facial Expression Recognition
Facial Expression Recognition Problem Description (12:21)
The class imbalance problem (6:03)
Utilities walkthrough (5:45)
Facial Expression Recognition in Code (Binary / Sigmoid) (12:13)
Facial Expression Recognition in Code (Logistic Regression Softmax) (8:57)
Facial Expression Recognition in Code (ANN Softmax) (10:44)
Extra Help
Gradient Descent Tutorial (4:30)
Help with Softmax Derivative (4:10)
Backpropagation with Softmax Troubleshooting (11:55)
Appendix
What order should I take your courses in? (pt 1) (11:18)
What order should I take your courses in? (pt 2) (16:07)
How to Code by Yourself (part 1) (15:54)
How to Code by Yourself (part 2) (9:23)
How to Succeed in this Course (Long Version) (10:24)
BONUS: Where to get discount coupons and FREE deep learning material (5:31)
Visualizing what a neural network has learned using TensorFlow Playground
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