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Bayesian Machine Learning in Python: A/B Testing Course

Bayesian Machine Learning in Python: A/B Testing Course
Bayesian Machine Learning in Python: A/B Testing Course

Bayesian Machine Learning in Python: A/B Testing Course

Data Science, Machine Learning, and Data Analytics Techniques for Marketing, Digital Media, Online Advertising, and More

What you’ll learn

Bayesian Machine Learning in Python: A/B Testing Course

  • Use adaptive algorithms to improve A/B testing performance
  • Understand the difference between Bayesian and frequentist statistics
  • Apply Bayesian methods to A/B testing

Requirements

  • Probability (joint, marginal, conditional distributions, continuous and discrete random variables, PDF, PMF, CDF)
  • Python coding with the Numpy stack

Description

This course is all about A/B testing.

Marketing, retail, newsfeeds, online advertising, and more.

A/B testing is all about comparing things.

Traditional A/B testing has been around for a long time, and it’s full of approximations and confusing definitions.

First, we’ll see if we can improve on traditional A/B testing with adaptive methods. These all help you solve the explore-exploit dilemma.

You’ll learn about the epsilon-greedy algorithm, which you may have heard about in the context of reinforcement learning.

We’ll improve upon the epsilon-greedy algorithm with a similar algorithm called UCB1.

Why is the Bayesian method interesting to us in machine learning?

It’s an entirely different way of thinking about probability.
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It’s a paradigm shift.

See you in class!

Suggested Prerequisites:

  • calculus
  • probability
  • Python coding: if/else, loops, lists, dicts, sets
  • Numpy, Scipy, Matplotlib

TIPS (for getting through the course):

  • Watch it at 2x.
  • Take handwritten notes. This will drastically increase your ability to retain the information.
  • Write down the equations. If you don’t, I guarantee it will just look like gibberish.
  • Ask lots of questions on the discussion board. The more the better!
  • Realize that most exercises will take you days or weeks to complete.
  • Write code yourself, don’t just sit there and look at my code.

WHAT ORDER SHOULD I TAKE YOUR COURSES IN?:

  • Check out the lecture “What order should I take your courses in?” (available in the Appendix of any of my courses, including the free Numpy course)

Who this course is for:

Bayesian Machine Learning in Python: A/B Testing Course

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