Part 1

Foundations

What is machine learning?

Introduce the language of machine learning before any predictive model appears.

A working definition

Machine learning is a way to build systems that improve at a task by learning patterns from data instead of being programmed with every rule by hand.

1. What Is Machine Learning?

Contrast hand-written rules with learned behaviour, then define models, parameters, training, inference, loss, and generalisation.

2. Datasets & Data Types

Understand observations, feature and label roles, data splits, and numerical, categorical, ordinal, text, time-series, and image data.

3. Types of Learning

When to use supervised, unsupervised, and reinforcement learning.

4. Exploratory Data Analysis

Inspect data quality, distributions, missing values, outliers, and early patterns before modelling.

5. Mathematical Foundations for Machine Learning

Vectors and matrices for representation, probability and statistics for uncertainty, and calculus for optimisation.