A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning

Full Stack Deep Learning Online Course

A PyTorch library for benchmarking deep metric learning. It's powerful.

Code base for the precision, recall, density, and coverage metrics for generative models. ICML 2020.

A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

TensorFlow implementation of the CVPR2020 paper: Disentangled Image Generation Through Structured Noise Injection

📝 Easily create a beautiful website using Academic, Hugo, and Netlify

A modular framework for vision & language multimodal research from Facebook AI Research (FAIR)

Code the the paper "Metric learning: cross-entropy vs. pairwise losses" (ECCV 2020 - Spotlight)

A guideline for building practical production-level deep learning systems to be deployed in real world applications.

Statistical Learning Theory (CS229T) Lecture Notes

[ICCV 2019] AutoGAN: Neural Architecture Search for Generative Adversarial Networks

Deep InfoMax (DIM), or "Learning Deep Representations by Mutual Information Estimation and Maximization"

A curated list of awesome self-supervised methods

A pytorch implementation of Maximum Mean Discrepancies(MMD) loss

🦍 Stanford CS236 : Deep Generative Models

GANs with spectral normalization and projection discriminator

Datasets, Transforms and Models specific to Computer Vision

A collection of works aiming at deploying NN in embedded systems

Embedded and mobile deep learning research resources

Building a scalable foundation for deep learning

http://nilhcem.com/android/custom-tensorflow-classifier

Computation using data flow graphs for scalable machine learning