An Open Source Machine Learning Framework for Everyone

Artificial Intelligence model trained with a CNN to detect fake images generated with AI using Deep learning.

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.

🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.

AI + Data, online. https://vespa.ai

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

A Python application, developed in Kivy, which enables mouse control using hand gestures through a webcam. This app uses MediaPipe hand tracking to feed a machine learing model to enhance gesture classification.

TFX is an end-to-end platform for deploying production ML pipelines

Implementing a Denoising Diffsuion Probabilistic Model (DDPM) on Tensorflow from scratch for Pokémon sprites synthesis

High-performance automatic differentiation of LLVM and MLIR.

Template designed to kickstart your machine learning projects in Python

AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet.

Self trained | transfer learning | AI built using Tensor flow

My first ML sandbox

This project leverages spotify's api and provided user playlists to create and tune a neural network model that generates song recommendations based off of song data in provided playlists.

A guidebook to explore Neural Networks.

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.

The Super-Resolution for Renewable Resource Data (sup3r) software uses generative adversarial networks to create synthetic high-resolution wind and solar spatiotemporal data from coarse low-resolution inputs.

This repository contains Dockerfiles, scripts, yaml files, Helm charts, etc. used to scale out AI containers with versions of TensorFlow and PyTorch that have been optimized for Intel platforms. Scaling is done with python, Docker, kubernetes, kubeflow, cnvrg.io, Helm, and other container orchestration frameworks for use in the cloud and on-premise

A retargetable MLIR-based machine learning compiler and runtime toolkit.