Machine Learning and Prediction: Decision Trees to Neural Networks - Part B

Learn essential machine learning concepts in this comprehensive FRM Part 1 tutorial covering decision trees, ensemble learning, classification methods, and neural networks. Master the construction and interpretation of decision trees, understand ensemble building techniques, and explore K-nearest neighbors and support vector machine classification methods. Delve into neural network architecture, weight determination processes, and performance evaluation using confusion matrices. Gain practical knowledge through examples and discover how to assess model effectiveness with receiver operating curves. Perfect for financial risk management professionals preparing for the FRM Part 1 exam, with content aligned to Chapter 15 of Book 2 in the 2025 curriculum.