There are 40 repositories under statistical-learning topic.
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。
Highly cited and useful papers related to machine learning, deep learning, AI, game theory, reinforcement learning
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.
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
An extensible framework for geospatial data science and geostatistical modeling fully written in Julia
My notes and codes (jupyter notebooks) for the "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani and Jerome Friedman
[PVLDB 2024 Best Paper Nomination] TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods
Solutions to labs and excercises from An Introduction to Statistical Learning, as Jupyter Notebooks.
Official Implementation of Early-Learning Regularization Prevents Memorization of Noisy Labels
Jupyter notebooks for summarizing and reproducing the textbook "The Elements of Statistical Learning" 2/E by Hastie, Tibshirani, and Friedman
Lecture Slides and R Sessions for Trevor Hastie and Rob Tibshinari's "Statistical Learning" Stanford course
TAPAS - Translational Algorithms for Psychiatry-Advancing Science
统计学习方法训练营课程作业及答案,视频笔记在线阅读地址:https://relph1119.github.io/statistical-learning-method-camp
A list of time-lasting classic books, which not only help you figure out how it works, but also grasp when it works and why it works in that way.
Solutions to exercises from Introduction to Statistical Learning (ISLR 1st Edition)
:book: List of some awesome university courses for Machine Learning! Feel free to contribute!
Materials to support learning with my YouTube channel, https://www.youtube.com/c/EquitableEquations.
Fixed Income Analytics, Portfolio Construction Analytics, Transaction Cost Analytics, Counter Party Analytics, Asset Backed Analytics
Introduction to Statistical Learning with R을 Python으로
Solutions to "An Introduction to Statistical Learning with Applications in R second edition"
Resources for education in statistics and machine learning: from advanced undergraduate to research level
:chart_with_upwards_trend: Machine Learning from the perspective of a Statistician using R