Introduction Machine Learning Algorithms by Khanna Vinod (18 results)

Condition: New.

Condition: New.

Condition: As New. Unread book in perfect condition.

Condition: As New. Unread book in perfect condition.

Condition: New.

Condition: New.

Condition: New.

HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.

HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.

Condition: New.

Hardback. Condition: New. Mathematics is the foundation of machine learning algorithms. To understand the shortcomings of existing algorithms and develop more effective methods, it is essential to understand the mathematical concepts underlying these algorithms and their operational principles. This book serves as an introductory resource, outlining the preliminary concepts and offering insights into the mathematical foundations and operational mechanisms of machine learning algorithms. It describes the basic equations and interrelates the questions arising during practical applications of machine learning with the basic mathematical picture of the algorithms used.Features. Introduces machine learning, highlights the central role of algorithms in machine learning, and explains the core mathematical prerequisites to understanding machine learning algorithms. Systematically examines the sequential steps of classical machine learning algorithms used for classification of data sets into distinct groups; regression, clustering analysis, Provides an overview of value, policy, and model-based reinforcement learning algorithms. This book is for academicians, scholars, students, and professionals engaged in the study of machine learning and artificial intelligence.…

Hardcover. Condition: Brand New. 440 pages. 9.18x6.12x9.45 inches. In Stock.

Hardback. Condition: New. Mathematics is the foundation of machine learning algorithms. To understand the shortcomings of existing algorithms and develop more effective methods, it is essential to understand the mathematical concepts underlying these algorithms and their operational principles. This book serves as an introductory resource, outlining the preliminary concepts and offering insights into the mathematical foundations and operational mechanisms of machine learning algorithms. It describes the basic equations and interrelates the questions arising during practical applications of machine learning with the basic mathematical picture of the algorithms used.Features. Introduces machine learning, highlights the central role of algorithms in machine learning, and explains the core mathematical prerequisites to understanding machine learning algorithms. Systematically examines the sequential steps of classical machine learning algorithms used for classification of data sets into distinct groups; regression, clustering analysis, Provides an overview of value, policy, and model-based reinforcement learning algorithms. This book is for academicians, scholars, students, and professionals engaged in the study of machine learning and artificial intelligence.…

Hardcover. Condition: new. Hardcover. Mathematics is the foundation of machine learning algorithms. To understand the shortcomings of existing algorithms and develop more effective methods, it is essential to understand the mathematical concepts underlying these algorithms and their operational principles. This book serves as an introductory resource, outlining the preliminary concepts and offering insights into the mathematical foundations and operational mechanisms of machine learning algorithms. It describes the basic equations and interrelates the questions arising during practical applications of machine learning with the basic mathematical picture of the algorithms used.Features Introduces machine learning, highlights the central role of algorithms in machine learning, and explains the core mathematical prerequisites to understanding machine learning algorithms Systematically examines the sequential steps of classical machine learning algorithms used for classification of data sets into distinct groups; regression, clustering analysis, Provides an overview of value, policy, and model-based reinforcement learning algorithms. This book is for academicians, scholars, students, and professionals engaged in the study of machine learning and artificial intelligence. Mathematics is the foundation of machine learning algorithms. To understand the shortcomings of existing algorithms and develop more effective methods, it is essential to understand the mathematical concepts underlying these algorithms and their operational principles. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Hardcover. Condition: new. Hardcover. Mathematics is the foundation of machine learning algorithms. To understand the shortcomings of existing algorithms and develop more effective methods, it is essential to understand the mathematical concepts underlying these algorithms and their operational principles. This book serves as an introductory resource, outlining the preliminary concepts and offering insights into the mathematical foundations and operational mechanisms of machine learning algorithms. It describes the basic equations and interrelates the questions arising during practical applications of machine learning with the basic mathematical picture of the algorithms used.Features Introduces machine learning, highlights the central role of algorithms in machine learning, and explains the core mathematical prerequisites to understanding machine learning algorithms Systematically examines the sequential steps of classical machine learning algorithms used for classification of data sets into distinct groups; regression, clustering analysis, Provides an overview of value, policy, and model-based reinforcement learning algorithms. This book is for academicians, scholars, students, and professionals engaged in the study of machine learning and artificial intelligence. Mathematics is the foundation of machine learning algorithms. To understand the shortcomings of existing algorithms and develop more effective methods, it is essential to understand the mathematical concepts underlying these algorithms and their operational principles. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Hardcover. Condition: new. Hardcover. Mathematics is the foundation of machine learning algorithms. To understand the shortcomings of existing algorithms and develop more effective methods, it is essential to understand the mathematical concepts underlying these algorithms and their operational principles. This book serves as an introductory resource, outlining the preliminary concepts and offering insights into the mathematical foundations and operational mechanisms of machine learning algorithms. It describes the basic equations and interrelates the questions arising during practical applications of machine learning with the basic mathematical picture of the algorithms used.Features Introduces machine learning, highlights the central role of algorithms in machine learning, and explains the core mathematical prerequisites to understanding machine learning algorithms Systematically examines the sequential steps of classical machine learning algorithms used for classification of data sets into distinct groups; regression, clustering analysis, Provides an overview of value, policy, and model-based reinforcement learning algorithms. This book is for academicians, scholars, students, and professionals engaged in the study of machine learning and artificial intelligence. Mathematics is the foundation of machine learning algorithms. To understand the shortcomings of existing algorithms and develop more effective methods, it is essential to understand the mathematical concepts underlying these algorithms and their operational principles. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Vinod Kumar Khanna, Ph.D. (Physics) is an emeritus scientist, Council of Scientific and Industrial Research (CSIR), India, and Emeritus Professor, Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India a retired chief scientist, .…

Buch. Condition: Neu. Introduction to Machine Learning Algorithms | Basic Principles and Mathematics | Vinod Kumar Khanna | Buch | Einband - fest (Hardcover) | Englisch | 2026 | Chapman and Hall/CRC | EAN 9781032725918 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.…