Guided Learning
Guided Pathways
Comprehensive deep-dives structured for sequential learning. From mathematical foundations to production implementations.
MA
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Series complete 7 Chapters
Mathematics for ML
This series bridges the gap between theoretical math and hands-on machine learning. From Linear Algebra to Information Theory.
ML
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Series complete 7 Chapters
MLOps for Time Series
A short series on building production-ready demand forecasting pipelines using classical models, ML enhancements and MLOps practices.
Chapter Overview
- 1 The Multi-Million Dollar Problem: Stockouts and Obsolete Stock
- 2 Our First Forecast: Traditional Time Series Models on Your Laptop
- 3 Beyond Tradition: Harnessing Machine Learning for Demand Forecasting
- 4 The MLOps Foundation: Structuring Our Project for Reproducibility and Collaboration
PR
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Series complete 6 Chapters
Practical Causal Inference for Finance
A comprehensive guide to determining true causation in financial data, featuring real-world applications of A/B testing, PSM, and advanced causal inference techniques.
Chapter Overview
- 1 Beyond Correlation: Why Your Business Metrics Are Lying to You
- 2 The Gold Standard: How AB Tests Work and When You Can't Use Them
- 3 The Magic of Mimicking Randomization: An Intro to Propensity Score Matching
- 4 PSM vs. IPW: A Practical Guide to Choosing Your Causal Method