Statistics - basics#

This material is part of the basics-books project. It is also available as a .pdf document.

Contents.

Introduction to statistics

Different approaches to statistics and descriptive statistics

Probability theory
Inferential statistics

Inferential and Bayesian statistics

Introduction to Machine Learning: SL, UL, ML

Machine learning (ML) is a branch of artificial intelligence (AI) focused on designing systems that can learn from data to improve their performance on a task. ML frameworks include supervised learning (e.g., regression and classification), unsupervised learning (e.g., clustering, compression, principal component analysis), and reinforcement learning (e.g., planning and control). ML emphasizes practical problem-solving, grounded in statistical methods, numerical optimization, and enabled by advances in computing hardware.