In this repository, I will implement some machine learning algorithms in Python, and show how to use it in a notebook. I feel it interesting and hope you can join me~

Code for my book on Multi-Armed Bandit Algorithms

Run MapReduce jobs on Hadoop or Amazon Web Services

Sample applications built using Amazon Machine Learning.

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 ;)

Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive lea…

Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Go, Javascript and more

Scalable, fast, and lightweight system for large-scale topic modeling

Large-scale and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, on single node, hadoop yarn and more.

Code for Kaggle Data Science Competitions

A python library for implementing a recommender system

Hashed Factorization Machine with Follow The Regularized Leader for Kaggle Avazu Click-Through Rate Competition

The implementation of some machine learning algorithms

Multi-armed bandit simulation library

Stanford Unsupervised Feature Learning and Deep Learning Tutorial

Applied Machine Learning in Python with scikit-learn