Machine Learning in Finance: From Theory to Practice Instructor’s Manual

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Machine Learning in Finance: From Theory to Practice Instructor's Manual Matthew F. Dixon, Igor Halperin and Paul Bilokon Introduction Advantage of the Book Recommended Course Syllabus Overview of the Textbook Exercises Python Notebooks Instructor Materials Part I Machine Learning with Cross-Sectional Data Introduction Probabilistic Modeling Bayesian Regression & Gaussian Processes Programming Related Questions* Feedforward Neural Networks Programming Related Questions* Interpretability Programming Related Questions* Part II Sequential Learning Sequence Modeling Probabilistic Sequence Modeling Advanced Neural Networks Programming Related Questions* Part III Sequential Data with Decision-Making Introduction to Reinforcement learning Applications of Reinforcement Learning Inverse Reinforcement Learning and Imitation Learning