This book offers a clear and steady introduction to how machines learn from data. It explains how models begin to understand, decide, improve, and sometimes falter.
This concise introduction to statistical modelling and machine learning focuses on core ideas and a carefully selected set... Læs mere
This book examines quantum neural networks through renormalization techniques,... Læs mere
This concise modern introduction to regression covers a wide range of topics and contemporary applications, including high-dimensional regression and causal inference, with concision... Læs mere
Reinforcement Learning (RL) is a branch of Artificial Intelligence (AI) that teaches agents to learn optimal behavior through interaction, feedback, and long-term goals.
This self-contained reference brings readers to the frontier of research on bandit convex optimization while presenting fundamental tools from convex optimization such as gradient-based algorithms, interior point methods and cutting plane methods.
Generative Artificial Intelligence is reshaping how we create, learn, and imagine. This book offers a clear and... Læs mere
The purpose of this Element is to introduce machine learning (ML) tools that can help asset managers discover economic and financial theories. ML is not a black box, and it does not necessarily overfit. ML tools complement rather than replace the classical statistical methods.
The text discusses theoretical background of algorithms and applications of methods using social science problems. It explores... Læs mere