statistical-learning

A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers.

An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code

Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies

The Elements of Statistical Learning (ESL)的中文翻译、代码实现及其习题解答。

A collection of research papers on decision, classification and regression trees with implementations.

This repository contains the exercises and its solution contained in the book "An Introduction to Statistical Learning" in python.

Highly cited and useful papers related to machine learning, deep learning, AI, game theory, reinforcement learning

《统计学习方法》笔记-基于Python算法实现

Teaching Materials for Dr. Waleed A. Yousef

A series of Python Jupyter notebooks that help you better understand "The Elements of Statistical Learning" book

Jupyter Notebooks for Springer book "Python for Probability, Statistics, and Machine Learning"

A comprehensive library for machine learning and numerical computing. The library provides a set of tools for linear algebra, numerical computing, optimization, and enables a generic, powerful yet still efficient approach to machine learning.

Machine Learning library for the web and Node.

An Introduction to Statistical Learning with Applications in PYTHON

My notes and codes (jupyter notebooks) for the "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani and Jerome Friedman

Jupyter notebooks for summarizing and reproducing the textbook "The Elements of Statistical Learning" 2/E by Hastie, Tibshirani, and Friedman

Official Implementation of Early-Learning Regularization Prevents Memorization of Noisy Labels

Lecture Slides and R Sessions for Trevor Hastie and Rob Tibshinari's "Statistical Learning" Stanford course

My book list

Solutions to labs and excercises from An Introduction to Statistical Learning, as Jupyter Notebooks.