Introduction to Machine Learning

What is Machine Learning?

Machine Learning (ML) is a subset of Artificial Intelligence that enables computers to learn from data without being explicitly programmed. Instead of writing rules, you provide examples and let the algorithm discover patterns.

"Machine learning is the field of study that gives computers the ability to learn without being explicitly programmed." — Arthur Samuel, 1959

Types of Machine Learning

1. Supervised Learning

The algorithm learns from labelled data — each example has an input and a known correct output.

2. Unsupervised Learning

The algorithm finds hidden patterns in unlabelled data.

• Clustering — Group similar customers (K-Means)
• Dimensionality Reduction — Compress data (PCA)

3. Reinforcement Learning

An agent learns by trial and error, receiving rewards for good actions.

• Used in: game playing (AlphaGo), robotics, self-driving cars

The Machine Learning Pipeline

Data Collection → Data Cleaning → Feature Engineering
→ Model Selection → Training → Evaluation → Deployment

Data Collection → Data Cleaning → Feature Engineering
→ Model Selection → Training → Evaluation → Deployment

Key Python Libraries for ML

Your First ML Taste

Run the code below to see a simple pattern recognition: