Stars
Learn how to design, develop, deploy and iterate on production-grade ML applications.
Perform data science on data that remains in someone else's server
A collaborative book on algorithms
Apache ECharts is a powerful, interactive charting and data visualization library for browser
🌿 Fast streaming XML parser written in C99 with >90% test coverage; moved from SourceForge to GitHub
All Algorithms implemented in Python
A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning al…
LIBSVM -- A Library for Support Vector Machines
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 comp…
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 …
CronHub is a better crontab, it is a web application which can schedule, monitor and control the crontabs of multiple machines from the web page.
a fast, scalable, multi-language and extensible build system
Collaborative Collection of C++ Best Practices. This online resource is part of Jason Turner's collection of C++ Best Practices resources. See README.md for more information.
The C++ Core Guidelines are a set of tried-and-true guidelines, rules, and best practices about coding in C++
Sarasra / models
Forked from tensorflow/modelsModels and examples built with TensorFlow
A toolkit for making real world machine learning and data analysis applications in C++
PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训练和跨平台部署）
scikit-learn: machine learning in Python
100+ Python challenging programming exercises
Data-Intensive Text Processing with MapReduce