ST310 (Machine Learning)
- Name: Domenico Mergoni
- Email: d.mergoni -at- lse.ac.uk
- Work: London School of Economics
Internet is a great resource. Use it. Some resources I like:
Course content (Official)
The primary focus of this course is on the core machine learning techniques in the context of high-dimensional or large datasets (i.e. big data). The first part of the course covers elementary and important statistical methods including nearest neighbours, linear regression, logistic regression, regularisation, cross-validation, and variable selection. The second part of the course deals with more advanced machine learning methods including regression and classification trees, random forests, bagging, boosting, deep neural networks, k-means clustering and hierarchical clustering. The course will also introduce causal inference motivated by analogy between double machine learning and two-stage least squares. All the topics will be delivered using illustrative real data examples. Students will also gain hands-on experience using R or Python (programming languages and software environments for data analysis, computing and visualisation).
Material and solutions
I did not write the following material, which was prepared by Joshua Loftus. My role was simply to present the content of the seminars and the solutions in class.
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