dgkim5360/the-elements-of-statistical-learning-notebooks
Jupyter notebooks for summarizing and reproducing the textbook "The Elements of Statistical Learning" 2/E by Hastie, Tibshirani, and Friedman
This project provides detailed Jupyter notebooks that break down and recreate the statistical learning techniques found in "The Elements of Statistical Learning" textbook. It takes the theoretical concepts from the book as input and produces working code examples and explanations. Data scientists, machine learning engineers, and statisticians seeking a deeper understanding of fundamental algorithms would find this useful.
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Use this if you are a data professional wanting to understand the core mechanics of statistical learning algorithms by seeing them implemented from scratch, rather than just using high-level libraries.
Not ideal if you're looking for a quick way to apply off-the-shelf machine learning models to your data, as this focuses on educational implementation rather than practical application.
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Last pushed
May 05, 2018
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