CS7CS4 – Machine Learning

Module CodeCS7CS4
Module NameMachine Learning
ECTS Weighting [1]5 ECTS
Semester TaughtSemester 1
Module Coordinator/s  Professor Douglas Leith

Module Learning Outcomes

On successful completion of this module, students will be able to:

  1. Understand what machine learning is and how it works;
  2. Understand and be able to apply machine learning algorithms such as linear regression, logistic regression, SVM, kNN and (deep) neural networks;
  3. Be able to effectively evaluate the performance of machine learning methods;
  4. Apply machine-learning frameworks (e.g. scikit-learn) to solve real-world problems;
  5. Write clear and effective reports to present machine learning results and analysis.

Module Content

  1. Prediction using machine learning;
  2. Choice of features, including for text, images, time series;
  3. Model selection (e.g. linear, kernel, neural net);
  4. Learning as empirical risk minimisation;
  5. Common machine learning techniques (linear regression, logistic regression, SVMs, kernel trick, neural nets, convolutional neural nets, kNN, k-Means);
  6. Evaluating machine learning methods (cross-validation, bootstrapping, ROC, use of a baseline);
  7. Practical experience of applying machine learning methods to real data;
  8. Experience of writing up machine learning analysis and results as a report.

Teaching and Learning Methods

Lectures and coursework.

Assessment Details

Assessment ComponentBrief DescriptionLearning Outcomes Addressed% of TotalWeek SetWeek Due

Coursework
Weekly Assignments;
Individual Project
LO1, LO2, LO3,
LO4, L05
100%Week 1TBC

Reassessment Details

Assignment (100%).

Contact Hours and Indicative Student Workload

Contact Hours (scheduled hours per student over full module), broken down by:22 hours
Lecture22 hours
Laboratory0 hours
Tutorial or seminar0 hours
Other0 hours
Independent study (outside scheduled contact hours), broken down by:94 hours
Preparation for classes and review of material (including preparation for examination, if applicable)44 hours
Completion of assessments (including examination, if applicable)50 hours
Total Hours116 hours

Recommended Reading List

N/A

Module Pre-requisite

Prerequisite modules: N/A

Other/alternative non-module prerequisites: Python programming.

Module Co-requisites

N/A

Module Website

Blackboard

Links to classes for the first two weeks (for students who may wish to switch to this module):

Blackboard collaborate link.

Lecture slides are available at: www.scss.tcd.ie/doug.leith/CSU44061.