Course Details
Country:
Netherlands
Institution:
Free University of Amsterdam
Course Title:
Machine Learning for Econometrics and Data Science
Course Number:
E_EDS3_MLEDS
Course Description:
Machine learning originates from computer science and statistics with the goal of exploring, studying, and developing learning systems, methods, and algorithms that can improve their performance by learning from data. This course is designed to provide students an introduction to the main foundations of machine learning. We adopt principles from probability (Bayes rule, conditioning, expectations, independence), linear algebra (vector and matrix operations), and calculus (gradients, Jacobians) to propose a formal analysis of the performance of machine learning algorithms. Focusing on the supervised learning framework, we formalise the problem of learning to predict based on a sample of 'examples'. We introduce the notions of predictor, generalisation risk, Bayes risk and target function, empirical risk, models and empirical risk minimisation, learning rules, approximation and estimation error decomposition, and derive learning guarantees under different classification and regression frameworks.
Language:
English
Approved Equivalent:
Pending For Approval
Attachment Files:
Studyguide (5)_11.pdf
