Tensors and Dynamic neural networks in Python with strong GPU acceleration

Python Data Science Handbook: full text in Jupyter Notebooks

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.

The fundamental package for scientific computing with Python.

Essential Cheat Sheets for deep learning and machine learning researchers https://medium.com/@kailashahirwar/essential-cheat-sheets-for-machine-learning-and-deep-learning-researchers-efb6a8ebd2e5

机器学习相关教程

Open Machine Learning Course

Parallel computing with task scheduling

阿布量化交易系统(股票，期权，期货，比特币，机器学习) 基于python的开源量化交易，量化投资架构

tensorboard for pytorch (and chainer, mxnet, numpy, ...)

中文 Python 笔记

NumPy aware dynamic Python compiler using LLVM

100 numpy exercises (with solutions)

A flexible framework of neural networks for deep learning

Trax — Deep Learning with Clear Code and Speed

NumPy-like API accelerated with CUDA

🤗nlp – Datasets and evaluation metrics for Natural Language Processing in NumPy, Pandas, PyTorch and TensorFlow

《利用Python进行数据分析·第2版》

🍊 📊 💡 Orange: Interactive data analysis https://orange.biolab.si

C++ tensors with broadcasting and lazy computing

人工智能学习路线图，整理近200个实战案例与项目，免费提供配套教材，零基础入门，就业实战！包括：Python，数学，机器学习，数据分析，深度学习，计算机视觉，自然语言处理，PyTorch tensorflow machine-learning,deep-learning data-analysis data-mining mathematics data-science artificial-intelligence python tensorflow tensorflow2 caffe keras pytorch algorithm numpy pandas matplotlib seaborn nlp cv等热门领域

Mars is a tensor-based unified framework for large-scale data computation which scales Numpy, Pandas and Scikit-learn.

N-D labeled arrays and datasets in Python

画像処理100本ノックして画像処理を画像処理して画像処理するためのもの Jap, Eng, Chi

Python Cheat Sheet NumPy, Matplotlib

Numpy exercises.

An open-access book on numpy vectorization techniques, Nicolas P. Rougier, 2017

Performance analysis of predictive (alpha) stock factors

Practice and tutorial-style notebooks covering wide variety of machine learning techniques

Những kiến thức cần thiết để học tốt Machine Learning trong vòng 2 tháng. Essential Knowledge for learning Machine Learning in two months.