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Translated[🔥updating ...] AI automated quantitative trading robot (fully local deployment) AI-powered Quantitative Investment Research Platform. 📃 online docs: https://ufund-me.github.io/Qbot ✨ :news: qbot-mini: https://github.com/Charmve/iQuant
This open-source curriculum introduces the fundamentals of Model Context Protocol (MCP) through real-world, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust and Python. Designed for developers, it focuses on practical techniques for building modular, scalable, and secure AI workflows from session setup to service orchestration.
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
Bringing stable diffusion models to web browsers. Everything runs inside the browser with no server support.
Apache Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.
An interactive data visualization tool which brings matplotlib graphics to the browser using D3.
WFGY is heading toward WFGY 5.0 Polaris Protocol, a major open-source release for AI reasoning, RAG, agents, and real-world workflows. Includes Problem Map, Global Debug Card, WFGY 4.0, and the CFV Easter Egg.
Complex code hides connections, workflows, and business risks.Unvibe complex code. Trace business workflows.
Collection of tools and code examples to demonstrate best practices in using Amazon EC2 Spot Instances.
Python API for Deequ
Pan-Cancer Integrative Histology-Genomic Analysis via Multimodal Deep Learning - Cancer Cell
Various Jupyter notebooks about Common Crawl data
Jupyterlab extension to show notebook cell completion notifications
UV-first benchmark for protein-ligand docking with reproducible annotation, pocket similarity, and HPC workflows.