Section 1 : Introduction and Outline
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Lecture 1 | What's this course all about | 00:03:55 Duration |
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Lecture 2 | Where to get the code for this course | 00:05:02 Duration |
Section 2 : The High-Level Picture
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Lecture 1 | Real-World Examples of AB Testing | 00:06:46 Duration |
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Lecture 2 | What is Bayesian Machine Learning | 00:11:33 Duration |
Section 3 : Bayes Rule and Probability Review
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Lecture 1 | Review Section Introduction | 00:01:22 Duration |
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Lecture 2 | Probability and Bayes' Rule Review | 00:05:27 Duration |
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Lecture 3 | Calculating Probabilities - Practice | 00:10:25 Duration |
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Lecture 4 | The Gambler | 00:05:42 Duration |
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Lecture 5 | The Monty Hall Problem | |
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Lecture 6 | Maximum Likelihood Estimation - Bernoulli | 00:11:43 Duration |
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Lecture 7 | Click-Through Rates (CTR) | 00:02:09 Duration |
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Lecture 8 | Maximum Likelihood Estimation - Gaussian (pt 1) | 00:10:07 Duration |
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Lecture 9 | Maximum Likelihood Estimation - Gaussian (pt 2) | 00:08:41 Duration |
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Lecture 10 | CDFs and Percentiles | 00:09:39 Duration |
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Lecture 11 | Probability Review in Code | 00:10:25 Duration |
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Lecture 12 | Probability Review Section Summary | 00:05:13 Duration |
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Lecture 13 | Beginners Fix Your Understanding of Statistics vs Machine Learning | 00:06:47 Duration |
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Lecture 14 | Anyone Can Succeed in this Course | 00:11:55 Duration |
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Lecture 15 | Suggestion Box | 00:03:04 Duration |
Section 4 : Traditional AB Testing
Section 5 : Bayesian AB Testing
Section 6 : Bayesian AB Testing Extension
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Lecture 1 | More about the Explore-Exploit Dilemma | 00:07:39 Duration |
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Lecture 2 | About Proctor Testing | |
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Lecture 3 | Adaptive Ad Server Exercise | 00:05:38 Duration |
Section 7 : Practice Makes Perfect
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Lecture 1 | Intro to Exercises on Conjugate Priors | 00:06:04 Duration |
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Lecture 2 | Exercise Die Roll | 00:02:38 Duration |
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Lecture 3 | The most important quiz of all - Obtaining an infinite amount of practice | 00:09:27 Duration |
Section 8 : Setting Up Your Environment (FAQ by Student Request)
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Lecture 1 | Windows-Focused Environment Setup 2018 | 00:20:20 Duration |
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Lecture 2 | How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow | 00:17:33 Duration |
Section 9 : Extra Help With Python Coding for Beginners (FAQ by Student Request)
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Lecture 1 | How to Code by Yourself (part 1) | 00:15:54 Duration |
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Lecture 2 | How to Code by Yourself (part 2) | 00:09:23 Duration |
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Lecture 3 | Proof that using Jupyter Notebook is the same as not using it | 00:12:29 Duration |
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Lecture 4 | Python 2 vs Python 3 | 00:04:28 Duration |
Section 10 : Effective Learning Strategies for Machine Learning (FAQ by Student Request)
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Lecture 1 | How to Succeed in this Course (Long Version) | |
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Lecture 2 | Is this for Beginners or Experts Academic or Practical Fast or slow-paced | 00:22:04 Duration |
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Lecture 3 | Machine Learning and AI Prerequisite Roadmap (pt 1) | 00:11:19 Duration |
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Lecture 4 | Machine Learning and AI Prerequisite Roadmap (pt 2) | 00:16:07 Duration |
Section 11 : Appendix FAQ Finale
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Lecture 1 | What is the Appendix | 00:02:48 Duration |