GitHub-проекты

An asynchronous engine for continuous & autonomous machine learning, built for real-time usage.

Toolkit for package and deploy machine learning models for serving in production

Machine Learning on Graphs, a Python library for machine learning on graph-structured (network-structured) data.

Examples and best practices for building recommendation systems, provided as Jupyter notebooks. The repo contains some of the latest state of the art algorithms from Microsoft Research as well as from other companies and institutions.

Machine Learning Prediction System on AWS Lambda

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

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.

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

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.

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

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

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

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

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 scikit-learn compatible neural network library that wraps PyTorch.

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

The lightweight PyTorch wrapper for high-performance AI research.

Tensors and Dynamic neural networks in Python with strong GPU acceleration

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

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.

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

Python bindings for Regularized Greedy Forest (Tree) Library.

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]

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

Machine learning toolkit focused on supervised classification. [Deprecated]

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

A python library for working with Probabilistic Graphical Models.

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.

Approximate nearest neighbours implementation.

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

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

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

Deep Learning In Python. [Deprecated]

Evolutionary algorithm framework.

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

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

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

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

Python Environment for Bayesian Learning. [Deprecated]

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]

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

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.

Open source platform for deploying machine learning models in production.

Theano based library for deep and recurrent neural networks.

Genetic algorithm framework. [Deprecated]

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.

Machine learning for NeuroImaging in Python.

Python implementation of cover trees, near-drop-in replacement for scipy.spatial.kdtree [Deprecated]