hsakas

Made-With-ML

Learn how to design, develop, deploy and iterate on production-grade ML applications.

ray

Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

jax

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

netron

Visualizer for neural network, deep learning and machine learning models

stanford-cs-229-machine-learning

VIP cheatsheets for Stanford's CS 229 Machine Learning

flair

A very simple framework for state-of-the-art Natural Language Processing (NLP)

dopamine

Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.

BigDL

Accelerate local LLM inference and finetuning (LLaMA, Mistral, ChatGLM, Qwen, Baichuan, Mixtral, Gemma, etc.) on Intel CPU and GPU (e.g., local PC with iGPU, discrete GPU such as Arc, Flex and Max). A PyTorch LLM library that seamlessly integrates with HuggingFace, LangChain, LlamaIndex, DeepSpeed, vLLM, FastChat, ModelScope, etc.

ignite

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

sacred

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

simple-faster-rcnn-pytorch

A simplified implemention of Faster R-CNN that replicate performance from origin paper

text

Models, data loaders and abstractions for language processing, powered by PyTorch

ELF

ELF: a platform for game research with AlphaGoZero/AlphaZero reimplementation

catalyst

Accelerated deep learning R&D

nnabla

Neural Network Libraries

coach

Reinforcement Learning Coach by Intel AI Lab enables easy experimentation with state of the art Reinforcement Learning algorithms

AutoSpotting

Saves up to 90% of AWS EC2 costs by automating the use of spot instances on existing AutoScaling groups. Installs in minutes using CloudFormation or Terraform. Convenient to deploy at scale using StackSets. Uses tagging to avoid launch configuration changes. Automated spot termination handling. Reliable fallback to on-demand instances.

gin-config

Gin provides a lightweight configuration framework for Python

faster_rcnn_pytorch

Faster RCNN with PyTorch

rust-ffi-examples

FFI examples written in Rust

fastprogress

Simple and flexible progress bar for Jupyter Notebook and console

neural-processes

This repository contains notebook implementations of the following Neural Process variants: Conditional Neural Processes (CNPs), Neural Processes (NPs), Attentive Neural Processes (ANPs).

densenet.pytorch

A PyTorch implementation of DenseNet.

nimtorch

PyTorch - Python + Nim

pytorch-tvmisc

Totally Versatile Miscellanea for Pytorch

cascade-rcnn_Pytorch

An implementation of Cascade R-CNN: Delving into High Quality Object Detection.

inferno

A utility library around PyTorch

numba_tutorial_scipy2017

Very-deep-cnn-pytorch

Very deep CNN for text classification

CondenseNet-PyTorch

A PyTorch Implementation for CondenseNet on Cifar10