Shapley Values for Explainable AI (The Course)
Explain Machine Learning Models With Shapley Values
This course teaches you one of the most powerful methods to explain predictions of machine learning models. Shapley values have a solid theoretical foundation in game theory and are model-agnostic — they can be applied to any machine learning model.
What the Course Will Teach You
- Understand and interpret Shapley values correctly.
- Hands-on application of Shapley values with R and Python
- Combining Shapley explanations to get global model interpretations such as feature importance, interactions and dependence plots.
- Optional: Deep dive into the mathematical and game-theoretical foundations.
Who is this Course for?
The course has three types of goals: building intuition, hands-on code examples and theoretical foundations. It‘s an all-inclusive package which should satisfy your needs, at whatever complexity you work with Shapley values. This course is for:
- Data Scientists who want to explain their model and build it into a dashboard.
- Researcher who want to find out what the heck their machine learning model learned.
- Machine learning engineers who make explanations part of their modeling pipeline.
- Operator of machine learning models that actually have to make sense of explanations that are produced by Shapley values.
Some Course Contents
- What are Shapley values?
- How can a prediction be explained with game theory?
- What the heck are SHAP, TreeSHAP, KernelSHAP?
- How do I use Shapley values in R or Python?
- How to combine individual explanations to get an understanding of the model behavior: Shapley based feature importance, interactions and dependence plots.
- How to apply Shapley values for text and image classification tasks.
- Shapley values and feature correlation.
- Creating model explanation dashboards quickly with shapash.
Why should you trust me (Christoph Molnar)?
- I have written a book about about various way to interpret machine learning models in a free online book on Interpretable Machine Learning.
- The book already has two chapters about Shapley values and SHAP. So you can check out if you like my style of explanation and trust me expertise.
- I have studied statistics and also worked as statistician. I have also done research about interpretable machine learning and worked as data scientist. I am positioned between academia and application, which is a good place to be to translate research into practical advice.
- I am not selling Shapley values as a miracle tool. I will be very honest about the situations in which they fail and what the caveats are.
On a mission to make algorithms more interpretable by combining machine learning and statistics.
The Leanpub 60-day 100% Happiness Guarantee
Within 60 days of purchase you can get a 100% refund on any Leanpub purchase, in two clicks.
See full terms
80% Royalties. Earn $16 on a $20 book.
We pay 80% royalties. That's not a typo: you earn $16 on a $20 sale. If we sell 5000 non-refunded copies of your book or course for $20, you'll earn $80,000.
(Yes, some authors have already earned much more than that on Leanpub.)
In fact, authors have earnedover $12 million USDwriting, publishing and selling on Leanpub.
Learn more about writing on Leanpub
Free Updates. DRM Free.
If you buy a Leanpub book, you get free updates for as long as the author updates the book! Many authors use Leanpub to publish their books in-progress, while they are writing them. All readers get free updates, regardless of when they bought the book or how much they paid (including free).
Most Leanpub books are available in PDF (for computers) and EPUB (for phones, tablets and Kindle). The formats that a book includes are shown at the top right corner of this page.
Finally, Leanpub books don't have any DRM copy-protection nonsense, so you can easily read them on any supported device.