Popular GitHub Repositories for Aws Ml Services

An Open Source Machine Learning Framework for Everyone

YOLOv5 ? in PyTorch > ONNX > CoreML > TFLite

100 Days of ML Coding

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

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

Visualizer for neural network, deep learning and machine learning models

Cross-platform, customizable ML solutions for live and streaming media.

Enhanced ChatGPT Clone: Features Agents, DeepSeek, Anthropic, AWS, OpenAI, Assistants API, Azure, Groq, o1, GPT-4o, Mistral, OpenRouter, Vertex AI, Gemini, Artifacts, AI model switching, message search, Code Interpreter, langchain, DALL-E-3, OpenAPI Actions, Functions, Secure Multi-User Auth, Presets, open-source for self-hosting. Active project.

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

JARVIS, a system to connect LLMs with ML community. Paper: https://arxiv.org/pdf/2303.17580.pdf

? A ranked list of awesome machine learning Python libraries. Updated weekly.

Open source platform for the machine learning lifecycle

Universal LLM Deployment Engine with ML Compilation

? The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools

Open standard for machine learning interoperability

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

A WebGL accelerated JavaScript library for training and deploying ML models.

The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.

VIP cheatsheets for Stanford's CS 229 Machine Learning

Welcome to the Llama Cookbook! This is your go to guide for Building with Llama: Getting started with Inference, Fine-Tuning, RAG. We also show you how to solve end to end problems using Llama model family and using them on various provider services