Code for Machine Learning for Trading, 3rd edition — from data sourcing to live execution.
- machine-learning
- trading
- investment
- finance
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Code for Machine Learning for Trading, 3rd edition — from data sourcing to live execution.
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.
Free MLOps course from DataTalks.Club. Register here 👇🏼 to get notified about the next cohort
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.
UV-first benchmark for protein-ligand docking with reproducible annotation, pocket similarity, and HPC workflows.