
Sách keo gáy, bìa mềm
This book is an introduction to machine learning,
with a strong focus on the mathematics behind the standard algorithms
and techniques in the field, aimed at senior undergraduates and early
graduate students of Mathematics.
There is a focus on well-known
supervised machine learning algorithms, detailing the existing theory to
provide some theoretical guarantees, featuring intuitive proofs and
exposition of the material in a concise and precise manner. A broad set
of topics is covered, giving an overview of the field. A summary of the
topics covered is: statistical learning theory, approximation theory,
linear models, kernel methods, Gaussian processes, deep neural networks,
ensemble methods and unsupervised learning techniques, such as
clustering and dimensionality reduction.
This book is suited for
students who are interested in entering the field, by preparing them to
master the standard tools in Machine Learning. The reader will be
equipped to understand the main theoretical questions of the current
research and to engage with the field.
Thể loại:Mathematics - Applied Mathematics
Năm:2024
In lần thứ:1
Ngôn ngữ:english
Trang:210