aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

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

A collection of various deep learning architectures, models, and tips

Your new Mentor for Data Science E-Learning.

The "Python Machine Learning (1st edition)" book code repository and info resource

An annotated implementation of the Transformer paper.

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

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its go…

Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.

BigDL: Distributed TensorFlow, Keras and PyTorch on Apache Spark/Flink & Ray

An interactive book on deep learning. Much easy, so MXNet. Wow. [Straight Dope is growing up] ---> Much of this content has been incorporated into the new Dive into Deep Learning Book available at …

《统计学习方法》笔记-基于Python算法实现

I took Andrew Ng's Machine Learning course on Coursera and did the homework assigments... but, on my own in python because I love jupyter notebooks!

1st place solution

Apache Spark & Python (pySpark) tutorials for Big Data Analysis and Machine Learning as IPython / Jupyter notebooks

动手学数据分析以项目为主线，知识点孕育其中，通过边学、边做、边引导来得到更好的学习效果

Causal Inference for the Brave and True的中文翻译版。全部代码基于Python，适用于计量经济学、量化社会学、策略评估等领域。英文版原作者：Matheus Facure

Implementation of Statistical Learning Method, Second Edition.《统计学习方法》第二版，算法实现。

Code of the IPython Cookbook, Second Edition, by Cyrille Rossant, Packt Publishing 2018 [read-only repository]

Step-by-step Deep Leaning Tutorials on Apache Spark using BigDL

Time Series Analysis & Forecasting of Rossmann Sales with Python. EDA, TSA and seasonal decomposition, Forecasting with Prophet and XGboost modeling for regression.

I used Machine Learning to make a Logistic Regression model using scikit-learn, pandas, numpy, seaborn and matplotlib to predict the results of FIFA 2018 World Cup.

💊 Comparing causality methods in a fair and just way.

Predict who will win the FIFA World Cup 2018

Tips for Advanced Feature Engineering

2019厦门国际银行“数创金融杯”数据建模大赛-top2

基于Python进行数据分析自动化的教程，同样的可以从中做出自己的自动生产报告的框架。

Predicting the winning team of the 2018 FIFA Wold Cup using BeautifulSoup and Pandas

Notebooks for Autodesk ADP Failure Prediction

梦想开始的地方