bn-pp

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.

VIP cheatsheets for Stanford's CS 221 Artificial Intelligence

Fast and Easy Infinite Neural Networks in Python

A Python library that helps data scientists to infer causation rather than observing correlation.

?? Visualize and control algorithms for the traveling salesman problem

A powerful, optimized and easy-to-use Java A* Pathfinding Library for 3D environments.

SparklingGraph provides easy to use set of features that will give you ability to proces large scala graphs using Spark and GraphX.

A web app to create and browse text visualizations for automated customer listening.

商品类目预测，使用 Spring Boot 开发框架和 Spark MLlib 机器学习框架，通过 TF-IDF 和 Bayes 算法，训练出一个商品类目预测模型。该模型可以根据商品名称自动预测出商品类目。项目对外提供 RESTFul 接口。