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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.

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

NumPy & SciPy for GPU

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.

A flexible framework of neural networks for deep learning

? Collection of Kaggle Solutions and Ideas ?

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

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