Python Deep-learning-models Resources

Spark NLP: State of the Art Natural Language Processing Spark NLP is a Natural Language Processing library built on top of Apache Spark ML. It provide

DeepPavlov is an open-source conversational AI library built on TensorFlow, Keras and PyTorch. DeepPavlov is designed for development of production re

An easier way to build neural search on the cloud Jina is a deep learning-powered search framework for building cross-/multi-modal search systems (e.g

GluonNLP: Your Choice of Deep Learning for NLP GluonNLP is a toolkit that helps you solve NLP problems. It provides easy-to-use tools that helps you l

OpenNMT-py: Open-Source Neural Machine Translation OpenNMT-py is the PyTorch version of the OpenNMT project, an open-source (MIT) neural machine trans

An Apache 2.0 NLP research library, built on PyTorch, for developing state-of-the-art deep learning models on a wide variety of linguistic tasks. Quic

torchtext This repository consists of: torchtext.data: Generic data loaders, abstractions, and iterators for text (including vocabulary and word vecto

A very simple framework for state-of-the-art NLP. Developed by Humboldt University of Berlin and friends. IMPORTANT: (30.08.2020) We moved our models

ChatterBot ChatterBot is a machine-learning based conversational dialog engine build in Python which makes it possible to generate responses based on

Rasa Open Source Rasa is an open source machine learning framework to automate text-and voice-based conversations. With Rasa, you can build contextual

Natural Language Toolkit (NLTK) NLTK -- the Natural Language Toolkit -- is a suite of open source Python modules, data sets, and tutorials supporting

State-of-the-art Natural Language Processing for PyTorch and TensorFlow 2.0 🤗 Transformers provides thousands of pretrained models to perform tasks o

spaCy: Industrial-strength NLP spaCy is a library for advanced Natural Language Processing in Python and Cython. It's built on the very latest researc

ivis Implementation of the ivis algorithm as described in the paper Structure-preserving visualisation of high dimensional single-cell datasets. Ivis

The open-source tool for building high-quality datasets and computer vision models. Website • Docs • Try it Now • Tutorials • Examples • Blog • Commun

AutoViz Automatically Visualize any dataset, any size with a single line of code. AutoViz performs automatic visualization of any dataset with one lin

In-depth EDA (target analysis, comparison, feature analysis, correlation) in two lines of code! Sweetviz is an open-source Python library that generat

openTSNE openTSNE is a modular Python implementation of t-Distributed Stochasitc Neighbor Embedding (t-SNE) [1], a popular dimensionality-reduction al

Introduction The facets project contains two visualizations for understanding and analyzing machine learning datasets: Facets Overview and Facets Dive

TensorFlow Data Validation TensorFlow Data Validation (TFDV) is a library for exploring and validating machine learning data. It is designed to be hig

UMAP Uniform Manifold Approximation and Projection (UMAP) is a dimension reduction technique that can be used for visualisation similarly to t-SNE, bu

Pandas Profiling Documentation | Slack | Stack Overflow Generates profile reports from a pandas DataFrame. The pandas df.describe() function is great

StarSpace StarSpace is a general-purpose neural model for efficient learning of entity embeddings for solving a wide variety of problems: Learning wor

Elegy Elegy is a framework-agnostic Trainer interface for the Jax ecosystem. Main Features Easy-to-use: Elegy provides a Keras-like high-level API tha

NeuPy v0.8.2 NeuPy is a python library for prototyping and building neural networks. NeuPy uses Tensorflow as a computational backend for deep learnin

MindsDB is an open-source AI layer for existing databases that allows you to effortlessly develop, train and deploy state-of-the-art machine learning

DISCONTINUATION OF PROJECT. This project will no longer be maintained by Intel. Intel will not provide or guarantee development of or support for this

Lasagne Lasagne is a lightweight library to build and train neural networks in Theano. Its main features are: Supports feed-forward networks such as C

dlib C++ library Dlib is a modern C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real worl

NeoML is an end-to-end machine learning framework that allows you to build, train, and deploy ML models. This framework is used by ABBYY engineers for

Documentations | Installation | Parameters | Python (scikit-learn) interface What's new? ThunderGBM won 2019 Best Paper Award from IEEE Transactions o

Note: We're moving to PyTorch Lightning! Read about the move here. From the end of February, torchbearer will no longer be actively maintained. We'll

Haiku: Sonnet for JAX Overview | Why Haiku? | Quickstart | Installation | Examples | User manual | Documentation | Citing Haiku What is Haiku? Haiku i

What's new We have recently released ThunderGBM, a fast GBDT and Random Forest library on GPUs. add scikit-learn interface, see here Overview The miss

Neural Tangents ICLR 2020 Video | Paper | Quickstart | Install guide | Reference docs | Release notes Overview Neural Tangents is a high-level neural

Documentation | FAQ | Release Notes | Roadmap | MACE Model Zoo | Demo | Join Us | 中文 Mobile AI Compute Engine (or MACE for short) is a deep learning i

fklearn: Functional Machine Learning fklearn uses functional programming principles to make it easier to solve real problems with Machine Learning. Th

The SHOGUN machine learning toolbox Unified and efficient Machine Learning since 1999. Latest release: Cite Shogun: Develop branch build status: Donat

What is xLearn? xLearn is a high performance, easy-to-use, and scalable machine learning package that contains linear model (LR), factorization machin

Overview | Tutorials | Examples | Installation | FAQ | How to Cite Welcome to ktrain News and Announcements 2020-11-08: ktrain v0.25.x is released and

This video in better quality. einops Flexible and powerful tensor operations for readable and reliable code. Supports numpy, pytorch, tensorflow, and

Translated in 🇰🇷 Korean/ Ludwig is a toolbox that allows users to train and test deep learning models without the need to write code. It is built on

a fast, flexible machine learning library Home | Documentation | Doxygen | Community | Help | IRC Chat Download: current stable version (3.4.2) mlpack

TL;DR Ignite is a high-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently. Click on the image to

A scikit-learn compatible neural network library that wraps PyTorch. Resources Documentation Source Code Examples To see more elaborate examples, look

CNTK Chat Windows build status Linux build status The Microsoft Cognitive Toolkit (https://cntk.ai) is a unified deep learning toolkit that describes

Sonnet Documentation | Examples Sonnet is a library built on top of TensorFlow 2 designed to provide simple, composable abstractions for machine learn

Tensorpack is a neural network training interface based on TensorFlow. Features: It's Yet Another TF high-level API, with speed, and flexibility built

Quick Links: Installation | Documentation | WWDC 2019 | WWDC 2018 Turi Create Check out our talks at WWDC 2019 and at WWDC 2018! Turi Create simplifie

English | 简体中文 Welcome to the PaddlePaddle GitHub. PaddlePaddle, as the only independent R&D deep learning platform in China, has been officially open

This is the Vowpal Wabbit fast online learning code. Why Vowpal Wabbit? Vowpal Wabbit is a machine learning system which pushes the frontier of machin

TFLearn: Deep learning library featuring a higher-level API for TensorFlow. TFlearn is a modular and transparent deep learning library built on top of

Chainer: A deep learning framework Website | Docs | Install Guide | Tutorials (ja) | Examples (Official, External) | Concepts | ChainerX Forum (en, ja

Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree

Thinc: A refreshing functional take on deep learning, compatible with your favorite libraries From the makers of spaCy, Prodigy and FastAPI Thinc is a

Welcome to fastai fastai simplifies training fast and accurate neural nets using modern best practices Important: This documentation covers fastai v2,

The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate. Website • Key Features • How To Use • Docs •

Apache MXNet (incubating) for Deep Learning Apache MXNet is a deep learning framework designed for both efficiency and flexibility. It allows you to m

Light Gradient Boosting Machine LightGBM is a gradient boosting framework that uses tree based learning algorithms. It is designed to be distributed a

eXtreme Gradient Boosting Community | Documentation | Resources | Contributors | Release Notes XGBoost is an optimized distributed gradient boosting l

Keras: Deep Learning for Python Under Construction In the near future, this repository will be used once again for developing the Keras codebase. For

About statsmodels statsmodels is a Python package that provides a complement to scipy for statistical computations including descriptive statistics an

PyTorch is a Python package that provides two high-level features: Tensor computation (like NumPy) with strong GPU acceleration Deep neural networks b

scikit-learn is a Python module for machine learning built on top of SciPy and is distributed under the 3-Clause BSD license. The project was started

Documentation TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, a

NO LONGER MAINTAINED This repository is no longer maintained due to lack of time. You might check out the fork https://github.com/mrevutskyi/flask-res

⚡ Create CRUD routes with lighting speed ⚡ A dynamic FastAPI router that automatically creates CRUD routes for your models Documentation: https://fast

lazydata: scalable data dependencies lazydata is a minimalist library for including data dependencies into Python projects. Problem: Keeping all data

Cache Machine Cache Machine provides automatic caching and invalidation for Django models through the ORM. For full docs, see https://cache-machine.re

Django Lifecycle Hooks This project provides a @hook decorator as well as a base model and mixin to add lifecycle hooks to your Django models. Django'

Django Cleanup Features The django-cleanup app automatically deletes files for FileField, ImageField and subclasses. When a FileField's value is chang

Django Countries A Django application that provides country choices for use with forms, flag icons static files, and a country field for models. Insta

django-money A little Django app that uses py-moneyed to add support for Money fields in your models and forms. Django versions supported: 1.11, 2.1,

AutoScraper: A Smart, Automatic, Fast and Lightweight Web Scraper for Python This project is made for automatic web scraping to make scraping easy. It

Pattern Pattern is a web mining module for Python. It has tools for: Data Mining: web services (Google, Twitter, Wikipedia), web crawler, HTML DOM par

Best-of Machine Learning with Python 🏆 A ranked list of awesome machine learning Python libraries. Updated weekly. This curated list contains 840 awe

Feedback Transformer - Pytorch Simple implementation of Feedback Transformer in Pytorch. They improve on Transformer-XL by having each token have acce

trRosetta - Pytorch (wip) Implementation of trRosetta and trDesign for Pytorch, made into a convenient package

FeatMatch: Feature-Based Augmentation for Semi-Supervised Learning This is the PyTorch implementation of our paper: FeatMatch: Feature-Based Augmentat

DALL-E in Pytorch Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch. It will also contain CLIP for ranking the ge

BudgetML is perfect for practitioners who would like to quickly deploy their models to an endpoint, but not waste a lot of time, money, and effort trying to figure out how to do this end-to-end.

PORORO: Platform Of neuRal mOdels for natuRal language prOcessing pororo performs Natural Language Processing and Speech-related tasks. It is easy to

Collection of tasks for fast prototyping, baselining, finetuning and solving problems with deep learning Installation

Deep Forest (DF) 21 DF21 is an implementation of Deep Forest 2021.2.1. It is designed to have the following advantages: Powerful: Better accuracy than

LIIF This repository contains the official implementation for LIIF introduced in the following paper: Learning Continuous Image Representation with Lo

Bottleneck Transformer - Pytorch Implementation of Bottleneck Transformer, SotA visual recognition model with convolution + attention that outperforms

Trankit: A Light-Weight Transformer-based Python Toolkit for Multilingual Natural Language Processing Trankit is a light-weight Transformer-based Pyth

说明 机器学习、深度学习、自然语言处理基础知识总结。 目前主要参考李航老师的《统计学习方法》一书，也有一些内容例如XGBoost、聚类、深度学习相关内容、NLP相关内容等是书中未提及的。

Flask App Builder Simple and rapid application development framework, built on top of Flask. includes detailed security, auto CRUD generation for your

Django Django is a high-level Python Web framework that encourages rapid development and clean, pragmatic design. Thanks for checking it out. All docu

GPT-NeoX An implementation of model parallel GPT-3-like models on GPUs, based on the DeepSpeed library. Designed to be able to train models in the hun

⚾ Automatically overlaying pitch motion and trajectory with machine learning! This project takes your baseball pitching clips and automatically genera

Deep Daze mist over green hills shattered plates on the grass cosmic love and attention a time traveler in the crowd life during the plague meditative

artificial intelligence cosmic love and attention fire in the sky a pyramid made of ice a lonely house in the woods marriage in the mountains lantern

Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting This is the origin Pytorch implementation of Informer in the followin

Learn X by doing Y 🛠️ Learn a technology X by doing a project Y Website You can contribute by adding projects to the CSV file.

Point Transformer - Pytorch Implementation of the Point Transformer self-attention layer, in Pytorch. The simple circuit above seemed to have allowed

WILDS is a benchmark of in-the-wild distribution shifts spanning diverse data modalities and applications, from tumor identification to wildlife monitoring to poverty mapping.

Graph Transformer Architecture Source code for the paper "A Generalization of Transformer Networks to Graphs" by Vijay Prakash Dwivedi and Xavier Bres

RLStructures is a lightweight Python library that provides simple APIs as well as data structures that make as few assumptions as possibl