NVIDIA Federated Learning Application Runtime Environment

Source code for the book "Math for Deep Learning" (No Starch Press)

Repo for Kedro Academy

AI Toolkit for Healthcare Imaging

The AI sensor processing SDK for low latency streaming workflows

Multi-modal agentic framework for surgical procedures

MONAI Label is an intelligent open source image labeling and learning tool.

MONAI Deploy App SDK offers a framework and associated tools to design, develop and verify AI-driven applications in the healthcare imaging domain.

MONAI Tutorials

MONAI Deploy Informatics Gateway facilitates integration with DICOM compliant systems, enables ingestion of imaging data, helps triggering of workflows with the MONAI Deploy Workflow Manager and of…

A set of common support code for medical imaging, surgical navigation, and related purposes.

An OSGi-like C++ dynamic module system and service registry

A Modern C++ Plugin Manager with Multi-Language Support

The official GitHub repository for the Mathematics of Machine Learning book!

Medical imaging toolkit for deep learning

A minimalist production ready plugin system

Open-source web application framework for ASP.NET Core! Offers an opinionated architecture to build enterprise software solutions with best practices on top of the .NET. Provides the fundamental in…

Polly is a .NET resilience and transient-fault-handling library that allows developers to express policies such as Retry, Circuit Breaker, Timeout, Bulkhead Isolation, and Fallback in a fluent and …

Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale.

Source code for the book "Math for Programming" (No Starch Press)

Simple, unambitious mediator implementation in .NET

Deep Learning Papers on Medical Image Analysis

Code for the book Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann.

This repo holds the code for the Udemy course: "Mastering Image Segmentation with PyTorch"

Python code (in the form of Jupyter ipython notebooks) to support the book "Math and Architectures of Deep Learning" (Krishnendu Chaudhury with Ananya Ashok, Sujay Narumanchi, Devashish Shankar).