Fast and Accurate ML in 3 Lines of Code

SIGKDD'2019: DeepGBM: A Deep Learning Framework Distilled by GBDT for Online Prediction Tasks

On the Variance of the Adaptive Learning Rate and Beyond

Collection of TensorFlow Examples

Debugging, monitoring and visualization for Python Machine Learning and Data Science

[CVPR2019] Fast Online Object Tracking and Segmentation: A Unifying Approach

Learning Latent Dynamics for Planning from Pixels

Latex code for making neural networks diagrams

Code for image generation of Variational Discriminator Bottleneck: Improving Imitation Learning, Inverse RL, and GANs by Constraining Information Flow

Code for the paper "Language Models are Unsupervised Multitask Learners"

Code for Switchable Normalization from "Differentiable Learning-to-Normalize via Switchable Normalization", https://arxiv.org/abs/1806.10779

A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas …

A PyTorch Extension: Tools for easy mixed precision and distributed training in Pytorch

A natural language modeling framework based on PyTorch

Python package built to ease deep learning on graph, on top of existing DL frameworks.

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

A re-implementation of "Prototypical Networks for Few-shot Learning"

Keras implementation of BERT with pre-trained weights

Google AI 2018 BERT pytorch implementation

Fast, modular reference implementation of Instance Segmentation and Object Detection algorithms in PyTorch.

Preparing for machine learning interviews

Largest multi-label image database; ResNet-101 model; 80.73% top-1 acc on ImageNet

TensorFlow Reinforcement Learning

Rethinking the Value of Network Pruning (Pytorch) (ICLR 2019)

A curated list of Meta-Learning resources/papers.

🌎 Simple and ready-to-use tutorials for TensorFlow

ICLR Reproducibility Challenge 2019

A programming language to skip the things you have already computed

Code to reproduce "imagenet in 18 minutes" DAWN-benchmark entry

An implementation of a Variational-Autoencoder using the Gumbel-Softmax reparametrization trick in TensorFlow (tested on r1.5 CPU and GPU) in ICLR 2017.