Module I:
Background and overview: Overview of terminology, formulations and concepts,
Introduction of main tasks, error and performance metrics, data preparation/annotation: Components of learning, data representation, linear classification, formulation of ML problem,

Module II:
Learnability: Hoeffding's inequality, overfitting, performance/complexity, bias/variance trade-off,
End-to-End Machine Learning Project: Feature selection, Feature transformation, model selection and validation, regularisation

Module III:
Regression: Linear Regression, Polynomial Regression, Logistic Regression, Regularized Linear Models, Logistic Regression

Module IV:
SVM and kernels: Hyperplane, separation with hard margin, soft margin, support vector classification, kernel methods, support vector regression

Module V:
Unsupervised learning: Clustering, k-means algorithm, PCA

To understand basic concepts, algorithms and techniques of machine learning.

To develop skills for analysing data and using it for training and deploying machine learning systems.

To gain understanding of software tools used for implementation of machine learning to solve challenges in healthcare sector.

At the end of the course, the student will be able to:
1. Gain foundational understanding of machine learning concepts.
2. Understand the different statistical and probabilistic concepts which enable machines to learn.
3. Develop data pre-processing pipelines for biological and healthcare data.
4. Develop machine learning models for classification and regression tasks required in healthcare applications.
5. Optimise machine learning models for better performance and easier translation for use in healthcare applications.

Hastie, Tibshirani, Freidman, The Element of Statistical Learning, Springer

Shai Shavlev and Shai Ben-David, Understanding Machine Learning, Cambridge University Press

Aurelien Geron, Hands-On Machine Learning with Sci-kit Learn, Keras and Tensorflow, O'Reilly

Ian Goodfellow, Yoshua Bengio, Aaron Courville, Deep Learning, The MIT Press, Cambridge Mass.