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.
Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
pandas on AWS - Easy integration with Athena, Glue, Redshift, Timestream, Neptune, OpenSearch, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL).
Learn how to design, develop, deploy and iterate on production-grade ML applications.
Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.
Real-time PathTracing with global illumination and progressive rendering, all on top of the Three.js WebGL framework. Click here for Live Demo: https://erichlof.github.io/THREE.js-PathTracing-Renderer/Geometry_Showcase.html
A toy physically based GPU path tracer (C++/OpenGL/GLSL)
A comprehensive guide to building RAG-based LLM applications for production.
A toolkit to run Ray applications on Kubernetes
RayLLM - LLMs on Ray
LuxCore source repository
NanoRT, single header only modern ray tracing kernel.
Dispatch and distribute your ML training to "serverless" clusters in Python, like PyTorch for ML infra. Iterable, debuggable, multi-cloud/on-prem, identical across research and production.
One repository is all that is necessary for Multi-agent Reinforcement Learning (MARL)
GPU Raytracer from scratch in C++/CUDA
DoEKS is a tool to build, deploy and scale Data & ML Platforms on Amazon EKS
A parallel framework for population-based multi-agent reinforcement learning.
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