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mxnet
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Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
State-of-the-art 2D and 3D Face Analysis Project
Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more
深度学习入门教程, 优秀文章, Deep Learning Tutorial
Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
Setup and customize deep learning environment in seconds.
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.
A GPU-accelerated library containing highly optimized building blocks and an execution engine for data processing to accelerate deep learning training and inference applications.
Probabilistic time series modeling in Python
An Engine-Agnostic Deep Learning Framework in Java
In this repository, I will share some useful notes and references about deploying deep learning-based models in production.
This project reproduces the book Dive Into Deep Learning (https://d2l.ai/), adapting the code from MXNet into PyTorch.
A high performance and generic framework for distributed DNN training
MLOps Tools For Managing & Orchestrating The Machine Learning LifeCycle
The convertor/conversion of deep learning models for different deep learning frameworks/softwares.
A Simple and Versatile Framework for Object Detection and Instance Recognition