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

Simple and Distributed Machine Learning

[ICCV 2021] A Pytorch implementation of "Manifold Matching via Deep Metric Learning for Generative Modeling"

Client side integration example source code and libraries for AI-Assisted Annotation SDK

Example code for integrating a custom data drift monitor into an MLOps solution using Azure Databricks and MLFlow.

Guideline for AI based Medical Devices

Python Script to download hundreds of images from 'Google Images'. It is a ready-to-run code!

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

This repository aims to map the ecosystem of artificial intelligence guidelines, principles, codes of ethics, standards, regulation and beyond.

YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet )

List of all the lessons learned, best practices, and links from my time studying machine learning

Implementations of CNNs, RNNs, GANs, etc

Hello AI World guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and NVIDIA Jetson.

Face Mask Detection using NVIDIA Transfer Learning Toolkit (TLT) and DeepStream for COVID-19

This is a sample application for counting people entering/leaving in a building using NVIDIA Deepstream SDK, Transfer Learning Toolkit (TLT), and pre-trained models. This application can be used to…

StyleGAN 2 in Tensorflow 2.0

AI Toolkit for Healthcare Imaging

A PyTorch Library for Accelerating 3D Deep Learning Research

Low-code framework for building custom LLMs, neural networks, and other AI models

An Open Source Machine Learning Framework for Everyone

Intel® AI Reference Models: contains Intel optimizations for running deep learning workloads on Intel® Xeon® Scalable processors and Intel® Data Center GPUs

A toolkit for developing and comparing reinforcement learning algorithms.

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

this repository accompanies the book "Grokking Deep Learning"

Pipeline for particle picking in cryo-electron microscopy images using convolutional neural networks trained from positive and unlabeled examples. Also featuring micrograph and tomogram denoising w…

TensorFlow's Visualization Toolkit

A Flow-based Generative Network for Speech Synthesis

The Triton Inference Server provides an optimized cloud and edge inferencing solution.

A GPU-accelerated library containing highly optimized building blocks and an execution engine for data processing to accelerate deep learning training and inference applications.

Deep Learning Tutorial for Kaggle Ultrasound Nerve Segmentation competition, using Keras