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Abstract algebra.

Contributor(s): Material type: TextTextPublisher: New York : 3G E-Learning, 2020Description: xiv, 314 pages : illustrations (some color) ; 27 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9781984637215
Subject(s): DDC classification:
  • 512.02 Ab892
LOC classification:
  • QA162
Contents:
Preliminaries -- Groups -- Rings -- Fields -- Some important theorems -- The fundamental theorem of Galois theory.
Summary: The concepts of Linear Algebra are crucial for understanding the theory behind Machine Learning, especially for Deep Learning. They give you better intuition for how algorithms really work under the hood, which enables you to make better decisions. Abstract algebra is a broad field of mathematics, concerned with algebraic structures such as groups, rings, vector spaces, and algebras. In a rough way, abstract algebra is the study of what happens when certain properties of number systems are abstracted out; for instance, altering the definitions od the basic arithmetic operations result in a structure known as a ring, so long as the operations are consistent. A certain amount of mathematical maturity is necessary to find and study applications of abstract algebra. A basic knowledge of set theory, mathematical induction, equivalence relations, and matrices is a must. Even more important is the ability to read and understant mathematical proofs. In this book, we will outline the background needed in abstract algebra.
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Holdings
Item type Current library Shelving location Call number Copy number Status Date due Barcode
Books Books Main Library Circulation Section CIR 512.02 Ab892 2020 (Browse shelf(Opens below)) 1-4 Available 022985
Books Books Main Library Circulation Section CIR 512.02 Ab892 2020 (Browse shelf(Opens below)) 2-4 Available 025627
Books Books Main Library Circulation Section CIR 512.02 Ab892 2020 (Browse shelf(Opens below)) 3-4 Available 025628
Books Books Main Library Circulation Section CIR 512.02 Ab892 2020 (Browse shelf(Opens below)) 4-4 Available 027866

Includes bibliographical references and index.

Preliminaries -- Groups -- Rings -- Fields -- Some important theorems -- The fundamental theorem of Galois theory.

The concepts of Linear Algebra are crucial for understanding the theory behind Machine Learning, especially for Deep Learning. They give you better intuition for how algorithms really work under the hood, which enables you to make better decisions. Abstract algebra is a broad field of mathematics, concerned with algebraic structures such as groups, rings, vector spaces, and algebras. In a rough way, abstract algebra is the study of what happens when certain properties of number systems are abstracted out; for instance, altering the definitions od the basic arithmetic operations result in a structure known as a ring, so long as the operations are consistent. A certain amount of mathematical maturity is necessary to find and study applications of abstract algebra. A basic knowledge of set theory, mathematical induction, equivalence relations, and matrices is a must. Even more important is the ability to read and understant mathematical proofs. In this book, we will outline the background needed in abstract algebra.

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