Episode 1 Telling the Computer What We Want Episode 2 Starting with Python Notebooks and Colab Episode 3 Decision Trees for Logical Rules Episode 4 Neural Networks for Perceptual Rules Episode 5 Opening the Black Box of a Neural Network Episode 6 Bayesian Models for Probability Prediction Episode 7 Genetic Algorithms for Evolved Rules Episode 8 Nearest Neighbors for Using Similarity Episode 9 The Fundamental Pitfall of Overfitting Episode 10 Pitfalls in Applying Machine Learning Episode 11 Clustering and Semi-Supervised Learning Episode 12 Recommendations with Three Types of Learning Episode 13 Games with Reinforcement Learning Episode 14 Deep Learning for Computer Vision Episode 15 Getting a Deep Learner Back on Track Episode 16 Text Categorization with Words as Vectors Episode 17 Deep Networks That Output Language Episode 18 Making Stylistic Images with Deep Networks Episode 19 Making Photorealistic Images with GANs Episode 20 Deep Learning for Speech Recognition Episode 21 Inverse Reinforcement Learning from People Episode 22 Causal Inference Comes to Machine Learning Episode 23 The Unexpected Power of Over-Parameterization Episode 24 Protecting Privacy within Machine Learning Episode 25 Mastering the Machine Learning Process.