#计算机科学#A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers.
#计算机科学#An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code
#计算机科学#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
翻译 - 将ML模型转换为零依赖的本机代码(Java,C,Python,Go,JavaScript,Visual Basic,C#)
#计算机科学#Highly cited and useful papers related to machine learning, deep learning, AI, game theory, reinforcement learning
翻译 - 与机器学习,深度学习,人工智能,博弈论,强化学习有关的高引用和有用论文
The Elements of Statistical Learning (ESL)的中文翻译、代码实现及其习题解答。
#计算机科学#A collection of research papers on decision, classification and regression trees with implementations.
翻译 - 有关决策,分类和回归树及其实现的研究论文的集合。
#计算机科学#This repository contains the exercises and its solution contained in the book "An Introduction to Statistical Learning" in python.
翻译 - 该存储库包含《 Python中的统计学习入门》一书中包含的练习及其解决方案。
#计算机科学#Teaching Materials for Dr. Waleed A. Yousef
#计算机科学#A series of Python Jupyter notebooks that help you better understand "The Elements of Statistical Learning" book
#计算机科学#A comprehensive library for machine learning and numerical computing. Apply Machine Learning with Rust leveraging first principles.
#计算机科学#Jupyter Notebooks for Springer book "Python for Probability, Statistics, and Machine Learning"
#计算机科学#Machine Learning library for the web and Node.
#计算机科学#An Introduction to Statistical Learning with Applications in PYTHON
An extensible framework for geospatial data science and geostatistical modeling fully written in Julia
#计算机科学#[PVLDB 2024 Best Paper Nomination] TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods
#计算机科学#My notes and codes (jupyter notebooks) for the "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani and Jerome Friedman
#计算机科学#Solutions to labs and excercises from An Introduction to Statistical Learning, as Jupyter Notebooks.
#计算机科学#Official Implementation of Early-Learning Regularization Prevents Memorization of Noisy Labels