ML4Trading from quantreo
What is ML4Trading?
Before we dive into the content, let me ask you this:Do you want to learn how to actually use Machine Learning in real trading, not just toy examples?
ML4Trading is the only course designed specifically to teach practical Machine Learning for quantitative trading, using real data, real targets, and real strategies.
It’s built around a field-tested methodology and a set of powerful tools I created from scratch to solve the exact problems most traders face when trying to use ML on financial markets.
With a structured methodology and advanced tools, you’ll be able to build a fully functional trading bot in less than 28 days .
ML4Trading is structured in 7 powerful modules, each one designed to help you go from raw market data to smart, robust, and automated Machine Learning trading strategies.
Intra-bar features (short-term price behavior, candle structure, micro-movements) Inter-bar features (technical indicators, statistical indicators, multi-bar logic) Over-bar features (trend filters, market regimes, macro view) Feature scaling, transformation, and stationarity Hurst exponent, autocorrelation, Yang-Zhang volatility estimator, and more20+ feature templates included
Learn how to create real, meaningful targets from market structure and price behavior Create multiple types of signals: candle color, trend continuation, volatility regime, and more Work with directional changes, triple barrier methods, and dummy labeling Understand the role of time horizons and outcome clarity Learn how to build ML targets that your models can actually learn from5+ ready-to-use target templates included
Walk-Forward Optimization, Monte Carlo and Robustness test. Perfect, test any strategies in a few minutes !
Use variance inflation factor (VIF) to remove multicollinearity Combine correlation, non-linear correlation, and mutual information Build a clean, structured dataset tailored to your signal Select only features that truly impact your target Avoid the classic trap of using “more data” instead of using “better data”Integrated with Quantreo’s feature selection tools !
Overview of linear vs. non-linear models Apply Random Forests, Extra Trees, Neural Networks, and SVMs to trading targets Learn which models fit which type of signal (trend vs. mean-reversion, volatility, regime detection) Build ensemble models with voting or bagging to improve robustness Understand the metrics that matter in trading (confusion matrix, PnL impact, trade frequency)+ All models fully coded and explained, nothing hidden, no guesswork
Avoid the black box trap: Learn how to analyze your model’s decisions with Shapley Values and feature importance. Focus on the metrics that matter for trading (not academic accuracy) — like precision by class, to protect your capital. Evaluate your models over multiple periods with Time Series Cross-Validation, not just a single backtest. Learn how to detect signal collapse early, before you waste time and money in live markets. Use specific signal analysis tools to find exactly where and why your model fails — and how to fix it.
“Why is my model wrong?” becomes “Here’s what to fix and how.”SECTION 6: CONDITION YOUR ANALYSIS
Learn to condition your signals based on market context, like volatility regimes, momentum strength, or technical setups Discover how to isolate the right moments to apply your model — instead of applying it blindly to every bar Filter out low-quality trades and increase model precision without changing the algorithm Build targeted signals that match specific market behaviors Learn how to combine data from multiple assets to train stronger, more generalizable models Increase the number of quality observations without introducing bias Avoid overfitting by testing your signals on correlated assets Build models that work across markets, not just on EUR/USD or BTC/USDT Develop advanced preprocessing workflows to balance targets and preserve structure
Today only, you can get lifetime access to ML4Trading for just $197.
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