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Books
Machine Learning
Projects
Machine Learning in Python for Quantitative Finance: Ecosystem and Lifecycle
Machine Learning in Practice: Yield Curves, Credit Risk, and SMOTE
Optimizing the Machine: Gradient Descent and Loss Landscapes
Deep Learning Foundations: Artificial Neural Networks in Finance
Finding the Edge: Support Vector Machines and the Kernel Trick
Sequential Mastery: AdaBoost, Gradient Boosting, and Pseudo-Residuals
The Power of the Crowd: Bagging and Stacking in Financial Markets
Introduction to Options and the Nature of Convexity
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