The Machine Learning Trading Bible

Transition from "Retailing Guessing" to "Quantitative Knowing"

Map the hierarchy of a $50M funded Edge

Set up the "Starter Kit" environment for production-grade research

A full ML trading system that covers ingestion, labeling, feature engineering, model training, validation, risk control, deployment-readiness monitoring, advanced techniques (AutoML, regime detection, deep learning

Text, Sentiment, and On-Chain - evaluates and integrates non-price data sources through NLP pipelines, sentiment scoring, on-chain metrics, and a data quality assessment framework

FX, Crypto, Futures - shows how the ML pipeline changes across asset classes, covering session effects, contract mechanics, execution differences, and the transferability framework