navneet-nmk

navneet-nmk's Stars

• donnemartin/system-design-primer

  Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.

  Language:Python271k45.7k

• kapilrathore/RxEventKit

  Reactive API for creating calendar events in iOS

  Language:Swift1

• huggingface/transformers

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

  Language:Python133k26.4k

• BlackHC/tfpyth

  Putting TensorFlow back in PyTorch, back in TensorFlow (differentiable TensorFlow PyTorch adapters).

  Language:Python64197

• navneet-nmk/Pytorch-RL-CPP

  A Repository with C++ implementations of Reinforcement Learning Algorithms (Pytorch)

  Language:C++9018

• numba/numba

  NumPy aware dynamic Python compiler using LLVM

  Language:Python9.8k1.1k

• yangshun/tech-interview-handbook

  💯 Curated coding interview preparation materials for busy software engineers

  Language:TypeScript117k14.6k

• iconix/openai

  OpenAI Scholar, general materials

  Language:Jupyter Notebook245

• jphall663/awesome-machine-learning-interpretability

  A curated list of awesome responsible machine learning resources.

  3.6k583

• osai-ai/tensor-stream

  A library for real-time video stream decoding to CUDA memory

  Language:C++37744

• jax-ml/jax

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

  Language:Python30.1k2.8k

• Lightning-AI/pytorch-lightning

  Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes.

  Language:Python28.1k3.4k

• bephrem1/interviewpen

  Code samples for Back to Back SWE lessons (archive).

  Language:Java1.8k790

• afshinea/stanford-cs-229-machine-learning

  VIP cheatsheets for Stanford's CS 229 Machine Learning

  17.5k3.9k

• ayir/machine_learning_kaggle

  Language:Jupyter Notebook1

• ayir/deepLearnigBasics

  This repository contains an introduction to deep learning models implemented in numpy and pytorch.

  Language:Jupyter Notebook2

• NVlabs/stylegan

  StyleGAN - Official TensorFlow Implementation

  Language:Python14.1k3.2k

• google-deepmind/grid-cells

  Implementation of the supervised learning experiments in Vector-based navigation using grid-like representations in artificial agents, as published at https://www.nature.com/articles/s41586-018-0102-6

  Language:Python24774

• tensorflow/tensorflow

  An Open Source Machine Learning Framework for Everyone

  Language:C++186k74.2k

• rddy/deeptutor

  Spaced repetition through deep reinforcement learning

  Language:Jupyter Notebook647

• navneet-nmk/Hierarchical-Meta-Reinforcement-Learning

  This repository contains the implementation for the paper - Exploration via Hierarchical Meta Reinforcement Learning.

  Language:Python604

• rail-berkeley/softlearning

  Softlearning is a reinforcement learning framework for training maximum entropy policies in continuous domains. Includes the official implementation of the Soft Actor-Critic algorithm.

  Language:Python1.2k238

• Farama-Foundation/Minigrid

  Simple and easily configurable grid world environments for reinforcement learning

  Language:Python2.1k603

• navneet-nmk/Disentangled-Map

  This repository contains the code for the implementation of the disentangled map representation in pytorch.

  Language:Python1

• jcjohnson/pytorch-examples

  Simple examples to introduce PyTorch

  Language:Python4.7k926

• navneet-nmk/Model-Agnostic-Variational-Exploration

  This repository contains the implementation for Model Agnostic Variational Exploration.

  Language:Python2

• tristandeleu/pytorch-maml-rl

  Reinforcement Learning with Model-Agnostic Meta-Learning in Pytorch

  Language:Python822157

• rtqichen/torchdiffeq

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

  Language:Python5.5k909

• openai/random-network-distillation

  Code for the paper "Exploration by Random Network Distillation"

  Language:Python872160

• navneet-nmk/Empowerment-driven-Exploration

  Tensorflow implementation for Empowerment driven Exploration using Mutual Information Estimation

  Language:Python71