A comprehensive library for machine learning and numerical computing. The library provides a set of tools for linear algebra, numerical computing, optimization, and enables a generic, powerful yet still efficient approach to machine learning.
created at May 8, 2019, 5:14 a.m.
An optimized graphs package for the Julia programming language
created at Jan. 15, 2015, 7:44 p.m.
A general classifier module to allow Bayesian and other types of classifications.
created at May 5, 2008, 5:24 p.m.
A Clojure high performance data processing system
created at Feb. 14, 2019, 5:07 p.m.
Tools for exploratory data analysis in Python
created at Feb. 16, 2016, 8:27 p.m.
Implementation/Tutorial of using Automated Machine Learning (AutoML) methods for static/batch and online/continual learning
created at Sept. 9, 2022, 3:01 a.m.
Python wrapper for Stanford CoreNLP tools v3.4.1
created at Feb. 26, 2011, 6:20 p.m.
The world's cleanest AutoML library ✨ - Do hyperparameter tuning with the right pipeline abstractions to write clean deep learning production pipelines. Let your pipeline steps have hyperparameter spaces. Design steps in your pipeline like components. Compatible with Scikit-Learn, TensorFlow, and most other libraries, frameworks and MLOps environments.
created at March 26, 2019, 9:01 p.m.
🐦 Opytimizer is a Python library consisting of meta-heuristic optimization algorithms.
created at Nov. 1, 2017, 4:04 p.m.
Collection of models for Core ML
created at June 8, 2017, 5:36 a.m.