a lightweight decision tree framework for Python with categorical feature support covering regular decision tree algorithms such as ID3, C4.5, CART, CHAID and regression tree; also some advanced bagging and boosting techniques such as gradient boosting, random forest and adaboost.
Book/iPython notebooks on Probabilistic Programming in Python.
A set of tools for creating and testing machine learning features, with a scikit-learn compatible API.
A Python module for metric learning.
Universal memory service with semantic search, autonomous consolidation, and multi-client support for AI applications.
A PyTorch-based framework to train and validate the models producing high-quality embeddings.
A seamless way to speed up your Scikit-learn applications with no accuracy loss and code changes.
Python implementation of many of the artificial intelligence algorithms described in the book "Artificial Intelligence, a Modern Approach". It focuses on providing an easy to use, well documented and tested library.
Enterprise-grade LLM integration framework for building production-ready AI applications with built-in hallucination prevention, RAG, and MCP support.
Numenta Platform for Intelligent Computing.
A Machine Learning library based on Theano. [Deprecated]
High-level neural networks frontend for TensorFlow, CNTK and Theano.
Lightweight library to build and train neural networks in Theano.
GPU-Accelerated Deep Learning Library in Python. [Deprecated]
Flexible neural network framework.
Python library for time series forecasting using machine learning models. It works with any regressor compatible with the scikit-learn API, including popular options like LightGBM, XGBoost, CatBoost, Keras, and many others.
Open source library with an exhaustive battery of feature engineering and selection methods based on pandas and scikit-learn.
A scikit-learn native toolkit for nonprofit and academic-medical-center fundraising analytics: leakage-safe donor propensity, lapse, planned-giving, wealth-screening and revenue-forecasting estimators.
Topic Modelling for Humans.
Interactive topic model visualization/interpretation framework.
Topic modelling toolkit. [Deprecated]
Another Python Machine Learning Library.
Fast, flexible and fun neural networks. This is the successor of PyBrain.
A flexible, fast recommender engine. [Deprecated]
A Python library for implementing a Recommender System.
Book on Bayesian Analysis.
Implementation of image to image (pix2pix) translation from the paper by isola et al.[DEEP LEARNING]
Restricted Boltzmann Machines in Python. [DEEP LEARNING]
Bolt Online Learning Toolbox. [Deprecated]
Python implementation of cover trees, near-drop-in replacement for scipy.spatial.kdtree [Deprecated]
Machine learning for NeuroImaging in Python.
Python toolbox for quick implementation, modification, evaluation, and visualization of ensemble learning algorithms for class-imbalanced data. Supports out-of-the-box multi-class imbalanced (long-tailed) classification.
Genetic algorithm framework. [Deprecated]
Theano based library for deep and recurrent neural networks.
Open source platform for deploying machine learning models in production.
library for approximate unsupervised inference in Bayesian Hidden Markov Models (HMMs) and explicit-duration Hidden semi-Markov Models (HSMMs), focusing on the Bayesian Nonparametric extensions, the HDP-HMM and HDP-HSMM, mostly with weak-limit approximations.