United Kingdom
Online Resource
Classical Machine Learning
An applied machine learning module building on Python programming and data handling skills. Learners implement supervised and unsupervised machine learning methods using scikit-learn, including classification algorithms, clustering and dimensionality reduction. The module covers model evaluation, performance improvement and robustness, and emphasises understanding why models work and what they reveal about data.
Keywords: classification, cross-validation, data summarisation, data visualisation, deep learning, feature engineering, machine learning, model evaluation, python, pytorch, regression, scikit-learn, statistics, supervised learning, unsupervised learnin
Target audience: Postgraduate researcher, Postgraduate student, Researcher, Clinician, Research Software Engineer, Bioinformatician, Research skills educator
Resource type: Online Resource
Version: 2025.1
Activity log
