neural-network

🎙Speech recognition using the tensorflow deep learning framework, sequence-to-sequence neural networks

JAX - A curated list of resources https://github.com/google/jax

C++ Implementation of PyTorch Tutorials for Everyone

텐서플로우를 기초부터 응용까지 단계별로 연습할 수 있는 소스 코드를 제공합니다

Machine learning on FPGAs using HLS

An End-To-End, Lightweight and Flexible Platform for Game Research

A Python toolkit/library for reality-centric machine/deep learning & data mining on partially-observed time series, with 50+ SOTA neural network model...

A Python package for extending the official PyTorch that can easily obtain performance on Intel platform

Recommender Learning with Tensorflow2.x

This is the code for Deformable Neural Radiance Fields, a.k.a. Nerfies.

An IPython Notebook tutorial on deep learning for natural language processing, including structure prediction.

Training PyTorch models with differential privacy

SLING - A natural language frame semantics parser

Deep learning in Rust, with shape checked tensors and neural networks

ML algorithms implemented and derived from first-principles in Jupyter Notebooks and NumPy

Generic U-Net Tensorflow implementation for image segmentation

Self-contained Machine Learning and Natural Language Processing library in Go

Machine Learning for Flappy Bird using Neural Network and Genetic Algorithm

AI on the way. An auto deep learning pipe dream. An RDBMS approach to deep learning. Declarative, explainable, scalable, optimizable, easy to deploy,...

PPL Quantization Tool (PPQ) is a powerful offline neural network quantization tool.

Awesome-pytorch-list 翻译工作进行中......

Official implementation of the RAVE model: a Realtime Audio Variational autoEncoder

Deep Learning and Machine Learning stocks represent promising opportunities for both long-term and short-term investors and traders.

Official github repository for Fast Artificial Neural Network Library (FANN)

A lightweight library for PyTorch training tools and utilities

PyTorch tutorials and best practices.

Acceleration package for neural networks on multi-core CPUs

Useful extra functionality for TensorFlow 2.x maintained by SIG-addons

NBA sports betting using machine learning

Building a Real-time Hand-Detector using Neural Networks (SSD) on Tensorflow

A PyTorch-based framework for Quantum Classical Simulation, Quantum Machine Learning, Quantum Neural Networks, Parameterized Quantum Circuits with sup...

A PyTorch library and evaluation platform for end-to-end compression research

GoMLX: An Accelerated Machine Learning Framework For Go

After watching all the videos of the famous Standford's CS231n course that took place in 2017, i decided to take summary of the whole course to help m...

A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods

A Data Streaming Library for Efficient Neural Network Training

Several simple examples for popular neural network toolkits calling custom CUDA operators.

Multi-class confusion matrix library in Python

A neural network library built in JavaScript

ARCHIVED: Contains historical course materials/Homework materials for the FREE MOOC course on "Creative Applications of Deep Learning w/ Tensorflow" #...

ChainerCV: a Library for Deep Learning in Computer Vision

PyTorch tutorials, examples and some books I found 【不定期更新】整理的PyTorch 最新版教程、例子和书籍

Slides and Jupyter notebooks for the Deep Learning lectures at Master Year 2 Data Science from Institut Polytechnique de Paris

Deep Learning Toolkit for Medical Image Analysis

Python programming assignments for Machine Learning by Prof. Andrew Ng in Coursera

List of Machine Learning, AI, NLP solutions for iOS. The most recent version of this article can be found on my blog.

A toolkit for time series machine learning and deep learning

Concise and beautiful algorithms written in Julia

Model explainability that works seamlessly with 🤗 transformers. Explain your transformers model in just 2 lines of code.

This repository contains small projects related to Neural Networks and Deep Learning in general. Subjects are closely linekd with articles I publish o...