Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more

State-of-the-art 2D and 3D Face Analysis Project

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

ncnn is a high-performance neural network inference framework optimized for the mobile platform

Open standard for machine learning interoperability

深度しんど学がく习入门教程ほど, 优秀文章ぶんしょう, Deep Learning Tutorial

State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.

TensorFlow Basic Tutorial Labs

Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.

This project reproduces the book Dive Into Deep Learning (https://d2l.ai/), adapting the code from MXNet into PyTorch.

Gluon CV Toolkit

A library for training and deploying machine learning models on Amazon SageMaker

MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.

Probabilistic time series modeling in Python

Setup and customize deep learning environment in seconds.

In this repository, I will share some useful notes and references about deploying deep learning-based models in production.

An Engine-Agnostic Deep Learning Framework in Java

《深度しんど学がく习与计算机つくえ视觉》配はい套代码

A GPU-accelerated library containing highly optimized building blocks and an execution engine for data processing to accelerate deep learning training and inference applications.

Machine Learning University: Accelerated Natural Language Processing Class