Shypd.aiThe largest open index of AI toolsREP is an open-source machine learning toolbox that provides a consistent and reproducible environment for data-driven research. It offers unified Python wrappers for various ML libraries and supports parallel training and smart grid-search algorithms.
Trending
Also listed in
About
REP, or Reproducible Experiment Platform, is an ipython-based environment designed for conducting data-driven research with an emphasis on consistency and reproducibility. It provides a unified Python wrapper for several machine learning libraries, including Sklearn, XGBoost, and Theanets, allowing users to work with a consistent interface. Key features include parallel training of classifiers on clusters, classification/regression reports with interactive plots, and smart grid-search algorithms with parallel execution. REP also supports research versioning using Git and offers pluggable quality metrics for classification. It aims to extend scikit-learn by providing a better user experience and tools for meta-algorithm design, making it a valuable resource for data scientists and researchers.
Capabilities
Pricing & Plans
Open Source
Free
FAQs
Trending
