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mRMR (minimum-Redundancy-Maximum-Relevance) for automatic feature selection at scale.

A flexible Federated Learning Framework based on PyTorch, simplifying your Federated Learning research.

基于Pytorch和torchtext的知识图谱深度学习框架。

SMT: The Surrogate Modeling Toolbox

Summary of deep learning models for dialog systems (Tiancheng Zhao LTI, CMU)

Python library assists deep learning on graphs

a reimplementation of Holistically-Nested Edge Detection in PyTorch

a reimplementation of PWC-Net in PyTorch that matches the official Caffe version

Algorithmic trading using heterogeneous graph neural network and reinforcement learning, pre-alpha

collection of super-resolution models & algorithms

推荐系统入门指南，全面介绍了工业级推荐系统的理论知识（王树森推荐系统公开课-基于小红书的场景讲解工业界真实的推荐系统），如何基于TensorFlow2训练模型，如何实现高性能、高并发、高可用的Golang推理微服务。Comprehensively introduced the theory of industrial recommender system, how to trainning models based on TensorFlow2, how to implement the high-performance、high-concurrency and high-available inference services base on Golang.

tensorflow for ruby

Ruby loader for the Stanford Sentiment Treebank (SST) parse trees and phrase labels, plus a locality-sensitive-hash index for word2vec binaries

PyTorch Python Index mirror with PEP 503 “simple” compliance updates

Tasks Assessing Protein Embeddings (TAPE), a set of five biologically relevant semi-supervised learning tasks spread across different domains of protein biology.

To be the world's best PyTorch project template.