An Open Source Machine Learning Framework for Everyone
Artificial Intelligence Deep Learning Machine Learning Tutorials
A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Climate / Energy, Automotives, Retail, Pharma, Medicine, Healthcare, Policy, Ethics and more.
Deep Learning Book
Repository for "Introduction to Artificial Neural Networks and Deep Learning: A Practical Guide with Applications in Python"
FlowNet3D: Learning Scene Flow in 3D Point Clouds (CVPR 2019)
A batteries-included kit for knowledge graphs
Medical image registration using deep learning
A PyTorch library and evaluation platform for end-to-end compression research
I try my best to keep updated cutting-edge knowledge in Machine Learning/Deep Learning and Natural Language Processing. These are my notes on some good papers
Machine learning games. Use combination of genetic algorithms and neural networks to control the behaviour of in-game objects.
Experimental tensor-typed deep learning
The SpeechBrain project aims to build a novel speech toolkit fully based on PyTorch. With SpeechBrain users can easily create speech processing systems, ranging from speech recognition (both HMM/DNN and end-to-end), speaker recognition, speech enhancement, speech separation, multi-microphone speech processing, and many others.
A multi-channel neural network audio classifier using Keras
A Keras CTC implementation of Baidu's DeepSpeech for model experimentation
A modern deep learning framework built to accelerate research and development of AI systems
Efficient, transparent deep learning in hundreds of lines of code.
Image Super Resolution
🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.
Tool for visualizing attention in the Transformer model (BERT, GPT-2, Albert, XLNet, RoBERTa, CTRL, etc.)
a delightful machine learning tool that allows you to train, test, and use models without writing code
An optical music recognition (OMR) system. Converts sheet music to a machine-readable version.
Implementing multilayer neural networks through backpropagation using Java.
A header-only C++ library for deep neural networks
Speech Enhancement Generative Adversarial Network in PyTorch
Deep & Classical Reinforcement Learning + Machine Learning Examples in Python
Bmw Yolov4 Inference Api Gpu
This is a repository for an nocode object detection inference API using the Yolov3 and Yolov4 Darknet framework.
A Hearthstone AI based on Monte Carlo tree search and neural nets written in modern C++.
Pyramidal Convolution: Rethinking Convolutional Neural Networks for Visual Recognition (https://arxiv.org/pdf/2006.11538.pdf)
Neural Adaptive Machine Translation that adapts to context and learns from corrections.
Toolkit to Hack Your Deep Learning Models
Deep Rl Trading
playing idealized trading games with deep reinforcement learning
U-Net implementation for PyTorch based on https://arxiv.org/abs/1505.04597
PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训练和跨平台部署）
NeMo: a toolkit for conversational AI
The library contains a number of interconnected Java packages that implement machine learning and artificial intelligence algorithms. These are artificial intelligence algorithms implemented for the kind of people that like to implement algorithms themselves.
Dimensionality reduction in very large datasets using Siamese Networks
My Awesome Ai Bookmarks
Curated list of my reads, implementations and core concepts of Artificial Intelligence, Deep Learning, Machine Learning by best folk in the world.
🏖 Easy training and deployment of seq2seq models.
Recurrent Neural Network and Long Short Term Memory (LSTM) with Connectionist Temporal Classification implemented in Theano. Includes a Toy training example.
Visualisation tool for CNNs in pytorch
A lightweight, portable pure C99 onnx inference engine for embedded devices with hardware acceleration support.
LaTeX/PDF + Epub version of the online book (http://neuralnetworksanddeeplearning.com) ”Neural Networks and Deep Learning“ by Michael Nielsen (@mnielsen)