licsh

AI-for-Security-Learning

安全场景、基于AI的安全算法和安全数据分析学习资料整理

Dive-into-DL-PyTorch

本项目将《动手学深度学习》（Dive into Deep Learning）原书中的MXNet代码实现改为PyTorch实现。

pyspark-tutorial

PySpark-Tutorial provides basic algorithms using PySpark

anomaly-detection-resources

Anomaly detection related books, papers, videos, and toolboxes

Autoencoders

awesome-automl-papers

A curated list of automated machine learning papers, articles, tutorials, slides and projects

Awesome-pytorch-list

A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.

Ax

Adaptive Experimentation Platform

BayesianOptimization

A Python implementation of global optimization with gaussian processes.

catboost

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

d2l-pytorch

This project reproduces the book Dive Into Deep Learning (www.d2l.ai), adapting the code from MXNet into PyTorch.

ds-cheatsheets

List of Data Science Cheatsheets to rule the world

gruvbox-contrib

Ports of the gruvbox colorscheme

hello-algo

《Hello 算法》是一本动画图解、能运行、可提问的数据结构与算法入门书，支持 Java, C++, Python, Go, JS, TS, C#, Swift, Zig 等语言。

hyperopt

Distributed Asynchronous Hyperparameter Optimization in Python

imbalanced-learn

A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning

leeml-notes

李宏毅《机器学习》笔记，在线阅读地址：https://datawhalechina.github.io/leeml-notes

Lihang

Statistical learning methods, 统计学习方法 [李航] 值得反复读. [笔记, 代码, notebook, 参考文献, Errata]

lihang-code

《统计学习方法》的代码实现

mlxtend

A library of extension and helper modules for Python's data analysis and machine learning libraries.

nni

An open source AutoML toolkit for neural architecture search and hyper-parameter tuning.

numpy-ml

Machine learning, in numpy

optuna

A hyperparameter optimization framework

pytorch-handbook

pytorch handbook是一本开源的书籍，目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门，其中包含的Pytorch教程全部通过测试保证可以成功运行

sklearn-porter

Transpile trained scikit-learn estimators to C, Java, JavaScript and others.

stanford-cs-229-machine-learning

VIP cheatsheets for Stanford's CS 229 Machine Learning

stanford-cs-230-deep-learning

VIP cheatsheets for Stanford's CS 230 Deep Learning

Statistical-Learning-Method_Code

手写实现李航《统计学习方法》书中全部算法

tensorflow-handbook

简单粗暴 TensorFlow 2.0 | A Concise Handbook of TensorFlow 2.0

tutorial