the-elements-of-statistical-learning
Jupyter notebooks implementing algorithms, proofs, and summaries from 'The Elements of Statistical Learning' textbook.
What is the-elements-of-statistical-learning?
The Elements of Statistical Learning notebooks is a collection of Jupyter notebooks that implement algorithms, proofs, and summaries from the classic textbook 'The Elements of Statistical Learning'. It provides practical code examples to help learners understand statistical learning concepts through hands-on experimentation.
Students, data scientists, and machine learning practitioners studying statistical learning who want to complement textbook reading with executable code implementations.
It offers a unique learning resource by providing runnable implementations of textbook algorithms, making abstract statistical learning concepts more accessible and practical compared to purely theoretical materials.
Overview
My notes and codes (jupyter notebooks) for the "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani and Jerome Friedman
Use Cases
Best For
- Studying statistical learning algorithms with practical code examples
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