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A wrapper around scikit-learn that makes it simpler to conduct experiments.

Spearmint is a package to perform Bayesian optimization according to the algorithms outlined in the paper: Practical Bayesian Optimization of Machine Learning Algorithms. Jasper Snoek, Hugo Larochelle and Ryan P. Adams. Advances in Neural Information Processing Systems, 2012. [Deprecated]

Python Environment for Bayesian Learning. [Deprecated]

Optimizing GPU-meta-programming code generating array oriented optimizing math compiler in Python.

Open source software library for numerical computation using data flow graphs.

Hidden Markov Models for Python, implemented in Cython for speed and efficiency.

A Python extension module wrapping the full TiMBL C++ programming interface. Timbl is an elaborate k-Nearest Neighbours machine learning toolkit.

Evolutionary algorithm framework.

Deep Learning In Python. [Deprecated]

A library consisting of useful tools for data science and machine learning tasks.

Nervana's high-performance Python-based Deep Learning framework [DEEP LEARNING]. [Deprecated]

Code samples for my book "Neural Networks and Deep Learning" [DEEP LEARNING].

Approximate nearest neighbours implementation.

Tool that automatically creates and optimizes machine learning pipelines using genetic programming. Consider it your personal data science assistant, automating a tedious part of machine learning.

A python library for working with Probabilistic Graphical Models.

The Deep Learning GPU Training System (DIGITS) is a web application for training deep learning models.

Machine learning toolkit focused on supervised classification. [Deprecated]

Deep learning library featuring a higher-level API for TensorFlow.

an IPython-based environment for conducting data-driven research in a consistent and reproducible way. REP is not trying to substitute scikit-learn, but extends it and provides better user experience. [Deprecated]

Python bindings for Regularized Greedy Forest (Tree) Library.

Python package for Bayesian Machine Learning with scikit-learn API.

Simple machine learning library, including Perceptron, Regression, Support Vector Machine, Decision Tree and more, it's easy to use and easy to learn for beginners.

A web-based application for quick, scalable, and automated hyperparameter tuning and stacked ensembling.

Tensors and Dynamic neural networks in Python with strong GPU acceleration

The lightweight PyTorch wrapper for high-performance AI research.

Toolbox of models, callbacks, and datasets for AI/ML researchers.

A scikit-learn compatible neural network library that wraps PyTorch.

Implementations of Machine Learning models from scratch in Python with a focus on transparency. Aims to showcase the nuts and bolts of ML in an accessible way.

A library for Restricted Boltzmann Machine (RBM) and its conditional variants in Tensorflow.

Implementation of machine learning stacking technique as a handy library in Python.

A modular active learning framework for Python, built on top of scikit-learn.

A Modern, Fast, and Modular Deep Learning and Machine Learning framework for Python.

A lightweight, NumPy-only autodiff library for small ML projects and learning how backpropagation works. It is 700x times lighter than Pytorch and 900x times lighter than TensorFlow.

Parris, the automated infrastructure setup tool for machine learning algorithms.

Machine learning from Apple. Turi Create simplifies the development of custom machine learning models. You don't have to be a machine learning expert to add recommendations, object detection, image classification, image similarity or activity classification to your app.

A high performance, memory efficient, maximally parallelized ensemble learning, integrated with scikit-learn.