Machine Learning Handbook
Year: 2025
Type: article
Abstract: This handbook offers a conceptual introduction to machine learning, intended for readers from diverse academic and professional backgrounds. It emphasizes understanding over implementation, focusing on the intuition behind key algorithms and methods—such as classification, regression, Bayesian models, and neural networks—without relying on programming or formal mathematics. Through illustrations, examples, and explanations, it serves as both a starting point for newcomers and a reference for common approaches in the field. The objective is to support interdisciplinary research by making machine learning concepts more accessible, encouraging collaboration across fields, and fostering more informed and reflective integration of these tools into various domains.
Author: Noriega Benitez, Enriqueta
Institution: Aalto University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7079670715
FWCI:
Cites:
Cited by:
Related to: