Streamlit is an open source app framework in Python language. It helps us create web apps for data science and machine learning in a short time.

Code for the paper "Jukebox: A Generative Model for Music"

A NLP platform to generate, summarize, rewrite, or classify texts in French and German.

Flyte is an open-source, container-native, structured programming and distributed processing platform implemented in Golang. It enables highly concurrent, scalable and maintainable workflows for machine learning and data processing.

Jina is a neural search framework that allows to build deep learning search applications in minutes. It provides scalable indexing, querying, understanding of any data: video, image, long/short text, music, source code, PDF, etc.

AI21 Studio allows users to generate text completions for an input prompt using Jurassic-1 language models.

EleutherAI is a decentralized grassroots collective of volunteer developers, engineers, and researchers focused on AI alignment, scaling, and open source AI research. Their flagship project is the GPT⁠-⁠Neo family of models designed to replicate those developed by OpenAI as GPT⁠-⁠3.

MIMIC is a web platform for the artistic exploration of musical machine learning and machine listening. We have designed this collaborative platform as an interactive online coding environment, engineered to bring new technologies in AI and signal processing to artists, composers, musicians and performers all over the world.

Sema is a playground where you can rapidly prototype live coding mini-languages for signal synthesis, machine learning and machine listening.

Sema aims to provide an online integrated environment for designing both abstract high-level languages and more powerful low-level languages.

A WebGL accelerated, browser based JavaScript library for training and deploying ML models. Use flexible and intuitive APIs to build and train models from scratch using the low-level JavaScript linear algebra library or the high-level layers API. Use TensorFlow.js model converters to run pre-existing TensorFlow models right in the browser. Retrain pre-existing ML models using sensor data connected to the browser, or other client-side data.

Kur is a system for quickly building and applying state-of-the-art deep learning models to new and exciting problems. Kur was designed to appeal to the entire machine learning community, from novices to veterans. It uses specification files that are simple to read and author, meaning that you can get started building sophisticated models without ever needing to code. Even so, Kur exposes a friendly and extensible API to support advanced deep learning architectures or workflows.

Chainer is a Python-based deep learning framework aiming at flexibility. It provides automatic differentiation APIs based on the define-by-run approach (a.k.a. dynamic computational graphs) as well as object-oriented high-level APIs to build and train neural networks. It also supports CUDA/cuDNN using CuPy for high performance training and inference.

Shogun is and open-source machine learning library that offers a wide range of efficient and unified machine learning methods.

Pyro is a universal probabilistic programming language (PPL) written in Python and supported by PyTorch on the backend. Pyro enables flexible and expressive deep probabilistic modeling, unifying the best of modern deep learning and Bayesian modeling.

A clear, concise, simple yet powerful and efficient API for deep learning.

An open-source NLP research library, built on PyTorch. AllenNLP makes it easy to design and evaluate new deep learning models for nearly any NLP problem, along with the infrastructure to easily run them in the cloud or on your laptop. AllenNLP includes reference implementations of high quality models for both core NLP problems (e.g. semantic role labeling) and NLP applications (e.g. textual entailment).

DeepForge is a development environment for deep learning designed for
simplicity, collaboration and reproducibility of experiments

Neural Models of Syntax.

A TensorFlow toolkit for deep learning powered natural language understanding (NLU).

Machine Learning in Python

Simple and efficient tools for data mining and data analysis
Accessible to everybody, and reusable in various contexts
Built on NumPy, SciPy, and matplotlib
Open source, commercially usable - BSD license

Open source machine learning tools for developers and product teams to expand bots beyond answering simple questions.

Rasa Core's primary purpose is to help you build contextual, layered conversations with lots of back-and-forth. To have a real conversation, you need to have some memory and build on things that were said earlier. Rasa Core lets you do that in a scalable way.

RASA NLU is an open-source tool for intent classification and entity extraction. You can think of it as a set of high level APIs for building your own language parser using existing NLP and ML libraries.