Books > Science & Mathematics > Mathematics > Optimization
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Convex Optimization for Machine Learning (Hardcover)
Loot Price: R3,086
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Convex Optimization for Machine Learning (Hardcover)
Series: NowOpen
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This book covers an introduction to convex optimization, one of the
powerful and tractable optimization problems that can be
efficiently solved on a computer. The goal of the book is tohelp
develop a sense of what convex optimization is, and how it can be
used in a widening array of practical contexts with a particular
emphasis on machine learning.The first part of the book covers core
concepts of convex sets, convex functions, and related basic
definitions that serve understanding convex optimization and its
corresponding models. The second part deals with one very useful
theory, called duality, which enables us to: (1) gain algorithmic
insights; and (2) obtain an approximate solution to non-convex
optimization problems which are often difficult to solve. The last
part focuses on modern applications in machine learning and deep
learning.A defining feature of this book is that it succinctly
relates the "story" of how convex optimization plays a role, via
historical examples and trending machine learning applications.
Another key feature is that it includes programming implementation
of a variety of machine learning algorithms inspired by
optimization fundamentals, together with a brief tutorial of the
used programming tools. The implementation is based on Python,
CVXPY, and TensorFlow. This book does not follow a traditional
textbook-style organization, but is streamlined via a series of
lecture notes that are intimately related, centered around coherent
themes and concepts. It serves as a textbook mainly for a
senior-level undergraduate course, yet is also suitable for a
first-year graduate course. Readers benefit from having a good
background in linear algebra, some exposure to probability, and
basic familiarity with Python.
General
Imprint: |
Now Publishers Inc
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Country of origin: |
United States |
Series: |
NowOpen |
Release date: |
September 2022 |
First published: |
2022 |
Authors: |
Changho Suh
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Dimensions: |
234 x 156 x 31mm (L x W x T) |
Format: |
Hardcover
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Pages: |
350 |
ISBN-13: |
978-1-63828-052-1 |
Languages: |
English
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Subtitles: |
English
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Categories: |
Books >
Science & Mathematics >
Mathematics >
Optimization >
General
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LSN: |
1-63828-052-5 |
Barcode: |
9781638280521 |
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