This chapter introduces some of the basic principles of Machine Learning and Artificial Intelligence for readers who may not have a strong quantitative background but already know a little about statistics and probability. The goal is to make complex concepts more accessible, with the broader intent of democratizing the comprehension and application of these methods within various fields of psychology. Because this is such a broad and fast-moving area, the chapter cannot go into every detail. Rather, the goal is to provide a strong starting point that helps readers continue learning on their own, while also sparking interest, creativity, and innovative applications in psychology.

Orsoni, M. (2026). A Concise Introduction to Machine Learning and Artificial Intelligence in Psychological Research. Bologna : Bologna University Press.

A Concise Introduction to Machine Learning and Artificial Intelligence in Psychological Research

Matteo Orsoni
Primo
Writing – Original Draft Preparation
2026

Abstract

This chapter introduces some of the basic principles of Machine Learning and Artificial Intelligence for readers who may not have a strong quantitative background but already know a little about statistics and probability. The goal is to make complex concepts more accessible, with the broader intent of democratizing the comprehension and application of these methods within various fields of psychology. Because this is such a broad and fast-moving area, the chapter cannot go into every detail. Rather, the goal is to provide a strong starting point that helps readers continue learning on their own, while also sparking interest, creativity, and innovative applications in psychology.
2026
Advanced Statistics for Psychology : A practical handbook for fundamentals and application
101
131
Orsoni, M. (2026). A Concise Introduction to Machine Learning and Artificial Intelligence in Psychological Research. Bologna : Bologna University Press.
Orsoni, Matteo
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/1051298
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