ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator

EBOP Model Automatic input Value Estimation Neural network

Supervisely SDK for Python - convenient way to automate, customize and extend Supervisely Platform for your computer vision task

Choice-Learn is a Python package designed to help you build with ease discrete choice models.

A Software Framework for Neuromorphic Computing

Neuromorphic mathematical optimization with Lava

Deep Learning library for Lava

Language modeling and instruction tuning for Russian

Bringing heterogenous hardware acceleration to Kotlin machine learning

Optimizing neural networks is crucial for achieving high performance in machine learning tasks. Optimization involves adjusting the weights and biases of the network to minimize the loss function. This process is essential for training deep learning models effectively and efficiently.

Explicitly Parameterized Neural Networks in Julia

High-efficiency floating-point neural network inference operators for mobile, server, and Web

Deep Learning for humans

Decentralized Asynchronous Training on Heterogeneous Devices

Deep Learning Simplified is an Open-source repository, containing beginner to advance level deep learning projects for the contributors, who are willing to start their journey in Deep Learning. Devfolio URL, https://devfolio.co/projects/deep-learning-simplified-f013

Dataset Management Framework, a Python library and a CLI tool to build, analyze and manage Computer Vision datasets.

Offers Neural Network Recognition (Yolov3) of IP Camerafeeds and signalling

Learn how modern, modular Neural Networks work by implementing a PyTorch/Keras-like framework.

The Hellenic Complex Systems Laboratory (HCSL) GitHub repository.

LLM training code for Databricks foundation models