Deep Learning

TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, and community resources that lets researchers push the state-of-the-art in ML and developers ea

Welcome to the Model Garden for TensorFlow The TensorFlow Model Garden is a repository with a number of different implementations of state-of-the-art (SOTA) models and modeling solutions for TensorFlow users. We aim t

Keras is an API designed for human beings, not machines. Keras follows best practices for reducing cognitive load: it offers consistent & simple APIs, it minimizes the number of user actions required for common use cases, and it p

PyTorch version of Google AI's BERT model with script to load Google's pre-trained models

PyTorch is a Python package that provides two high-level features: Tensor computation (like NumPy) with strong GPU acceleration Deep neural networks built on a tape-based autograd system You can reuse your favorite Py

TensorFlow Examples This tutorial was designed for easily diving into TensorFlow, through examples. For readability, it includes both notebooks and source codes with explanation, for both TF v1 & v2. It is suitable

deepfakes_faceswap FaceSwap is a tool that utilizes deep learning to recognize and swap faces in pictures and videos. Jennifer Lawrence/Steve Buscemi FaceSwap using the Villain model Make sure you che

An updated and organized reading list for illustrating the patterns of scalable, reliable, and performant large-scale systems. Concepts are explained in the articles of prominent engineers and credible references. Case studies are

100-Days-Of-ML-Code 100 Days of Machine Learning Coding as proposed by Siraj Raval Get the datasets from here Data PreProcessing | Day 1 Check out the code from here. Simple Linear Regression

Deep Learning Papers Reading Roadmap If you are a newcomer to the Deep Learning area, the first question you may have is "Which paper should I start reading from?" Here is a reading roadmap of Deep Learning pap

BERT ***** New March 11th, 2020: Smaller BERT Models ***** This is a release of 24 smaller BERT models (English only, uncased, trained with WordPiece masking) referenced in Well-Read Students Learn Better: On the Impor

A practical approach to learning machine learning.

Basics 🔥 Among the top 10 ML repos on GitHub Learn Python basics with notebooks. Use data science libraries like NumPy

More than 95% of deepfake videos are created with DeepFaceLab. DeepFaceLab is used by such popular youtube channels as

Status: Maintenance (expect bug fixes and minor updates) OpenAI Gym OpenAI Gym is a toolkit for developing and comparing reinforcement learning algorithms. This is the gym open-source library, which gives you access

Detectron Detectron is Facebook AI Research's software system that implements state-of-the-art object detection algorithms, including Mask R-CNN. It is written in Python and powered by the Caffe2 deep learning frame

This project aims at teaching you the fundamentals of Machine Learning in python. It contains the example code and solutions to the exercises in my O'Reilly book Hands-on Machine Learning with Scikit-Learn and TensorFlow

Awesome - Most Cited Deep Learning Papers [Notice] This list is not being maintained anymore because of the overwhelming amount of deep learning papers published every day since 2017. A curated list of the most cited

waifu2x Image Super-Resolution for Anime-style art using Deep Convolutional Neural Networks. And it supports photo. The demo application can be found at http://waifu2x.udp.jp/ . Note that I only provide this website a

This repository provides tutorial code for deep learning researchers to learn PyTorch. In the tutorial, most of the models were implemented with less than 30 lines of code. Before starting this tutorial, it is recommended to f

data-science-ipython-notebooks Index deep-learning tensorflow theano keras caffe scikit-learn statistical-inference-scipy pandas matplotlib numpy python-data

fastai The fastai library simplifies training fast and accurate neural nets using modern best practices. See the fastai website to get started. The library is based on research into deep learning best practices

spaCy: Industrial-strength NLP spaCy is a library for advanced natural language processing in Python and Cython. spaCy is built on the very latest research, but it isn't researchware. It was designed from day one to

Mask R-CNN for Object Detection and Segmentation This is an implementation of Mask R-CNN on Python 3, Keras, and TensorFlow. The model generates bounding boxes and segmentation masks for each instance of an object in th

Machine Learning From Scratch About Python implementations of some of the fundamental Machine Learning models and algorithms from scratch. The purpose of this project is not to produce as optimized and compu

Homemade Machine Learning For Octave/MatLab version of this repository please check machine-learning-octave project. This repository contains examples of popular machine learning algorithms implemented in

Project DeepSpeech DeepSpeech is an open source Speech-To-Text engine, using a model trained by machine learning techniques based on Baidu's Deep Speech research paper. Project DeepSpeech uses Google's TensorFlow t

neural-style This is a torch implementation of the paper A Neural Algorithm of Artistic Style by Leon A. Gatys, Alexander S. Ecker, and Matthias Bethge. The paper presents an algorithm for combining the content of one

Detectron2 is FAIR's next-generation research platform for object detection and segmentation.

About Spleeter is the Deezer source separation library with pretrained models written in Python and uses Tensorflow. It makes it easy to train source separation model (assuming you have a dataset of isolated

Overview This repository provides code, exercises and solutions for popular Reinforcement Learning algorithms. These are meant to serve as a learning tool to complement the theoretical materials from Reinforcement L

Magenta is a project from the Google Brain team that asks: Can we use machine learning to create compelling art and music? If so, how? If not, why not? We’ll use TensorFlow, and we’ll release our models and tools in open source

A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.