Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

深度学习入门教程, 优秀文章, Deep Learning Tutorial

Interview = 简历指南 + 算法题 + 八股文 + 源码分析

PyTorch implementation of the U-Net for image semantic segmentation with high quality images

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.

数据挖掘、计算机视觉、自然语言处理、推荐系统竞赛知识、代码、思路

🏅 Collection of Kaggle Solutions and Ideas 🏅

A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Climate / Energy, Automotives, Retail, Pharma, Medicine, Healthcare, Policy, Ethics and more.

免费学代码系列：小白python入门、数据分析data analyst、机器学习machine learning、深度学习deep learning、kaggle实战

1st place solution

1st Place Solution for CrowdFlower Product Search Results Relevance Competition on Kaggle.

PyTorch extensions for fast R&D prototyping and Kaggle farming

A searchable compilation of Kaggle past solutions

MLBox is a powerful Automated Machine Learning python library.

CatBoost tutorials repository

LAMA - automatic model creation framework

DataScience projects for learning : Kaggle challenges, Object Recognition, Parsing, etc.