Gokula Krishnan

schedule_free. Schedule-Free Optimization in PyTorch

LLM-Workshop. LLM Workshop by Sourab Mangrulkar

llm-course. Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.

ml-engineering. Machine Learning Engineering Open Book

Awesome-Multimodal-Large-Language-Models. :sparkles::sparkles:Latest Advances on Multimodal Large Language Models

FlexLLMGen. Running large language models on a single GPU for throughput-oriented scenarios.

prmonitor. A browser extension to keep track of incoming and outgoing PRs

cosmopolitan. build-once run-anywhere c library

firefly-iii. Firefly III: a personal finances manager

vit-pytorch. Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch

fucking-algorithm. Crack LeetCode, not only how, but also why.

blog-o-matic. Fork this repo so that you can, after following instructions, have a quick blog setup on github pages with Pelican static generator and Elegant theme

hyper. HTTP/2 for Python.

docker_programming_station. A simple script to help programmers who want to work within Docker

awesome-reMarkable. A curated list of projects related to the reMarkable tablet

interviews. Everything you need to know to get the job.

awesome-competitive-programming. :gem: A curated list of awesome Competitive Programming, Algorithm and Data Structure resources

cityhash. Automatically exported from code.google.com/p/cityhash

cloudpickle. Extended pickling support for Python objects

Megalodon. Various ML/DL Resources organised at a single place.

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

cifar-10h. Original dataset release for CIFAR-10H

pytudes. Python programs to practice and demonstrate skills

python-is-cool. Cool Python features for machine learning that I used to be too afraid to use. Will be updated as I have more time / learn more.

pytorch-vq-vae. PyTorch implementation of VQ-VAE by Aäron van den Oord et al.

WideResNet-pytorch. Wide Residual Networks (WideResNets) in PyTorch

the-incredible-pytorch. The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch.

PyTorch_CIFAR10. Pretrained TorchVision models on CIFAR10 dataset (with weights)

awesome-machine-learning-interpretability. A curated list of awesome responsible machine learning resources.

awesome-mlss. 🤖 Machine Learning Summer School Guide

a_bite_on_tf. HTML

nitrain. Train AI models efficiently on medical images using any framework

ignite. High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.

shap. A game theoretic approach to explain the output of any machine learning model.

pyBreakDown. Python implementation of R package breakDown

easygen. Python

Grokking-Deep-Learning. this repository accompanies the book "Grokking Deep Learning"

detect-timeseriesdata-change. WARNING: This repository is no longer maintained :warning: This repository will not be updated. The repository will be kept available in read-only mode.

TSML.jl. A package for time series data processing, classification, clustering, and prediction.

pytorchpipe. PyTorchPipe (PTP) is a component-oriented framework for rapid prototyping and training of computational pipelines combining vision and language

ZOO-Attack. Codes for reproducing the black-box adversarial attacks in “ZOO: Zeroth Order Optimization based Black-box Attacks to Deep Neural Networks without Training Substitute Models,” ACM CCS Workshop on AI-Security, 2017

CNN-Cert. Codes for reproducing the experimental results in "CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks", published at AAAI 2019

tensorflow-large-model-support. Large Model Support in Tensorflow

matrix-capsules-with-em-routing. A TensorFlow implementation of "Matrix Capsules with EM Routing" by Hinton et al. (2018).

awesome-very-deep-learning. ♾A curated list of papers and code about very deep neural networks

repo-badges. :star: Use repo badges (build passing, coverage, etc) in your readme/markdown file to signal code quality in a project.

pasta. Library to refactor python code through AST manipulation.

innvestigate. A toolbox to iNNvestigate neural networks' predictions!

awesome-multimodal-ml. Reading list for research topics in multimodal machine learning

SO-mod-userscripts. Stack Overflow Moderation Userscripts

pytorch-unet. Simple PyTorch implementations of U-Net/FullyConvNet (FCN) for image segmentation

gans-from-theory-to-production. Material for the tutorial: "Deep Diving into GANs: from theory to production"

adversarial_example. A simple adversarial attack on a linear model

binarygan. Code for "Training Generative Adversarial Networks with Binary Neurons by End-to-end Backpropagation"

icecream. 🍦 Never use print() to debug again.

tech-interview-handbook. Curated coding interview preparation materials for busy software engineers

xgboost. Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow

vowpal_wabbit. Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.

pytorch-sentiment-analysis. Tutorials on getting started with PyTorch and TorchText for sentiment analysis.

vim-python-ide. Python development config

cookiecutter. A cross-platform command-line utility that creates projects from cookiecutters (project templates), e.g. Python package projects, C projects.

matrix-sqrt. matrix square root and its gradient

BigGAN-PyTorch. The author's officially unofficial PyTorch BigGAN implementation.

paper-tips-and-tricks. Best practice and tips & tricks to write scientific papers in LaTeX, with figures generated in Python or Matlab.

stockpredictionai. In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.

strans. Performs string manipulation tasks by learning from the provided example(s), instead of having to program them out explicitly.

causal-inference-intro. A short introduction to causal inference

open-source-cs. Video discussing this curriculum:

DEC-keras. Keras implementation for Deep Embedding Clustering (DEC)

adv-eval-paper. LaTeX source for the paper "On Evaluating Adversarial Robustness"

PlotNeuralNet. Latex code for making neural networks diagrams

Tensorflow-Cookbook. Simple Tensorflow Cookbook for easy-to-use

cs228-notes. Course notes for CS228: Probabilistic Graphical Models.

Matrix-Calculus-Tutorial. Matrix Calculus via Differentials, Matrix Derivative, 矩阵求导教程

ImageNet-Adversarial-Training. ImageNet classifier with state-of-the-art adversarial robustness

tf2_course. Notebooks for my "Deep Learning with TensorFlow 2 and Keras" course

deep-learning-drizzle. Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!

mushroom-rl. Python library for Reinforcement Learning.

ffhq-dataset. Flickr-Faces-HQ Dataset (FFHQ)

wide-residual-networks. 3.8% and 18.3% on CIFAR-10 and CIFAR-100

snorkel. A system for quickly generating training data with weak supervision

retro. Retro Games in Gym

python-fire. Python Fire is a library for automatically generating command line interfaces (CLIs) from absolutely any Python object.

pi-hole. A black hole for Internet advertisements

telegrad. A Telegram bot to monitor and control deep learning experiments

amld-pytorch-workshop. Introduction to PyTorch Workshop at the AMLD 2019

xgboostExplainer. An R package that makes xgboost models fully interpretable

DeepReinforcementLearning. A replica of the AlphaZero methodology for deep reinforcement learning in Python

SOM-VAE. TensorFlow implementation of the SOM-VAE model as described in https://arxiv.org/abs/1806.02199

scientific_python_cheat_sheet. simple overview of python, numpy, scipy, matplotlib functions that are useful for scientific work

gtop. System monitoring dashboard for terminal

bottom-up-attention-vqa. An efficient PyTorch implementation of the winning entry of the 2017 VQA Challenge.

imgaug. Image augmentation for machine learning experiments.

pytorch-custom-dataset-examples. Some custom dataset examples for PyTorch

stanford-cs-230-deep-learning. VIP cheatsheets for Stanford's CS 230 Deep Learning

TPR-RNN. Code for the publication Learning to Reason with Third-Order Tensor Products.

sacredboard. Dashboard for sacred. Monitor and access your past machine learning experiments.

dynamic-training-bench. Simplify the training and tuning of Tensorflow models

sacred. Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.

randopt. Streamlined machine learning experiment management.

ducttape. A workflow management system for researchers who heart Unix.

git-crecord. Git subcommand to interactively select changes to commit or stage

baselines. OpenAI Baselines: high-quality implementations of reinforcement learning algorithms

jax. Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

SnapchatClone. Java

adversarial-logit-pairing-analysis. Analysis of Adversarial Logit Pairing

Women-Engineers-India-Ultimate-List. A crowdsourced list of all the amazing women engineers in India!

TensorFlow-Tuts. TensorFlow Tutorials in making

tensorflow_cookbook. Code for Tensorflow Machine Learning Cookbook

plaidml. PlaidML is a framework for making deep learning work everywhere.

ray. Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

rllab. rllab is a framework for developing and evaluating reinforcement learning algorithms, fully compatible with OpenAI Gym.

semantic-embeddings. Hierarchy-based Image Embeddings for Semantic Image Retrieval

big-list-of-naughty-strings. The Big List of Naughty Strings is a list of strings which have a high probability of causing issues when used as user-input data.

torchdiffeq. Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.

MentisOculi. A raytracer written in PyTorch (raynet?)

diffai. A certifiable defense against adversarial examples by training neural networks to be provably robust

ELINA. ELINA: ETH LIbrary for Numerical Analysis

eran. ETH Robustness Analyzer for Deep Neural Networks

waveglow. A Flow-based Generative Network for Speech Synthesis

deep-learning-v2-pytorch. Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101

hyperopt. Distributed Asynchronous Hyperparameter Optimization in Python

deepfloat. An exploration of log domain "alternative floating point" for hardware ML/AI accelerators.

ml-videos. A collection of video resources for machine learning

Learn-Something-Every-Day. 📝 A compilation of everything that I learn; Computer Science, Software Development, Engineering, Math, and Coding in General. Read the rendered results here ->

magical_universe. Awesome Python features explained using the world of magic

presentations. Collection of presentations for advanced Python topics

python-patterns. A collection of design patterns/idioms in Python

PyTricks. Collection of less popular features and tricks for the Python programming language

awful-ai. 😈Awful AI is a curated list to track current scary usages of AI - hoping to raise awareness

google-research. Google Research

yewtube. yewtube, forked from mps-youtube , is a Terminal based YouTube player and downloader. No Youtube API key required.

awesome-ai-residency. List of AI Residency Programs

nlp_course. YSDA course in Natural Language Processing

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

tf-explorer. A command-line interface tool to explore TensorFlow checkpoints.

summerschool2015. Slides and exercises for the Deep Learning Summer School 2015 programming tutorials

summerschool2016. Montréal Deep Learning Summer School 2016 material

summerschool2017. Material for the Montréal Deep Learning Summer School 2017

tana. This Aint No AutoML

mltest. Testing framework to simplify writing ML unit tests.

models. Models and examples built with TensorFlow

python_voc_parser. Python

keras-applications. Reference implementations of popular deep learning models.

setup.py. 📦 A Human's Ultimate Guide to setup.py.

DeepRL. Modularized Implementation of Deep RL Algorithms in PyTorch

state-of-the-art-result-for-machine-learning-problems. This repository provides state of the art (SoTA) results for all machine learning problems. We do our best to keep this repository up to date. If you do find a problem's SoTA result is out of date or missing, please raise this as an issue or submit Google form (with this information: research paper name, dataset, metric, source code and year). We will fix it immediately.

lab. A customisable 3D platform for agent-based AI research

trfl. TensorFlow Reinforcement Learning

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

nvtop. GPU & Accelerator process monitoring for AMD, Apple, Huawei, Intel, NVIDIA and Qualcomm

vel. Velocity in deep-learning research

agent. Interpretability dashboard for reinforcement learners

ml-agents. The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.

pytorch-maml. PyTorch implementation of MAML: https://arxiv.org/abs/1703.03400

pytudes. Python programs, usually short, of considerable difficulty, to perfect particular skills.

tensorboardX. tensorboard for pytorch (and chainer, mxnet, numpy, ...)

fast-wavenet. Speedy Wavenet generation using dynamic programming :zap:

self-attention-gan. Python

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

pytorch-web-deploy. Simple, fast web deployment for your PyTorch models

Practical_RL. A course in reinforcement learning in the wild

wavegan. WaveGAN: Learn to synthesize raw audio with generative adversarial networks

literate-raytracer. a literate raytracer in javascript

Stabilizing_GANs. Code for the NIPS17 paper "Stabilizing Training of Generative Adversarial Networks through Regularization"

Neural-Network-in-Haskell. Haskell

gan-toolkit. The aim of the toolkit is to provide a highly flexible, no-code way of implementing GAN models.

Things-a-scientist-is-suppposed-to-know. A comprehensive and long list of things a modern scientist is supposed to know

reinforcement-learning. Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.

stable-baselines. A fork of OpenAI Baselines, implementations of reinforcement learning algorithms

xcessiv. A web-based application for quick, scalable, and automated hyperparameter tuning and stacked ensembling in Python.

tf-eager-examples. A set of simple examples ported from PyTorch for Tensorflow Eager Execution

poincare_embeddings. NumPy implementation of Poincaré Embeddings for Learning Hierarchical Representations (Facebook Research)

scripts-to-rule-them-all. Set of boilerplate scripts describing the normalized script pattern that GitHub uses in its projects.

DeepMind-Atari-Deep-Q-Learner. The original code from the DeepMind article + my tweaks

openmp-little-book. A little book which introduces OpenMP C/C++ concurrency programming.

python-nameless. Sample project. Use https://github.com/ionelmc/cookiecutter-pylibrary to make your own project. The purpose of this repo is to test the CI configuration.

julia-introduction. Two-day introduction course to Julia programming language

NYU-DLSP20. NYU Deep Learning Spring 2020

adversarial-robustness-toolbox. Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams

numerical-linear-algebra. Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course

2048-deep-reinforcement-learning. Trained A Convolutional Neural Network To Play 2048 using Deep-Reinforcement Learning

awesome-interpretable-machine-learning. Python

higgsfield. Fault-tolerant, highly scalable GPU orchestration, and a machine learning framework designed for training models with billions to trillions of parameters

Kind-PyTorch-Tutorial. Kind PyTorch Tutorial for beginners

the-gan-zoo. A list of all named GANs!

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

build-your-own-x. Master programming by recreating your favorite technologies from scratch.

handson-ml. ⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 or handson-mlp instead.

ML_course. EPFL Machine Learning Course, Fall 2025

unbounded_gan. Improve generative adversarial network training by deleting a line of code.

pytorch-examples. Simple examples to introduce PyTorch

TensorFlow-Tutorials. TensorFlow Tutorials with YouTube Videos

caffe-tensorflow. Caffe models in TensorFlow

caffe2tf. Define TensorFlow networks using Caffe proto files.

oneDNN. oneAPI Deep Neural Network Library (oneDNN)

coding-interview-university. A complete computer science study plan to become a software engineer.

iml. iml: interpretable machine learning R package

All-About-the-GAN. All About the GANs(Generative Adversarial Networks) - Summarized lists for GAN

np-hard-deep-reinforcement-learning. pytorch neural combinatorial optimization