Artificial Intelligence and Machine Learning: Theory and Practice - Couverture souple

Das, Lyla B.; George, Sudhish N.; Aprem, Anup

Couverture souple

ISBN 10 : 9390620090 ISBN 13 : 9789390620098

Editeur : TechSar Pvt. Ltd, 2023

Synopsis

This book is designed for undergraduates, postgraduates and professionals who want to have a firm grip on the fundamental principles of AI and ML.

Artificial Intelligence (AI) is a broad area of knowledge which has percolated into every aspect of human life. 'Machine Learning algorithms' are considered to be a subset of AI Theory, mathematics and coding are three aspects to any topic in AI. This book covers the most relevant topics in the field of Artificial Intelligence and Machine Learning (ML).

The subdivisions of Machine Learning are Supervised, Unsupervised and Reinforcement learning. All three are covered in sufficient depth. One very important and upcoming field of application is Natural Language Processing (NLP). A whole section of the book has been devoted to this.
br>The book covers the conceptual, mathematical and numerical analysis of the important ML algorithms and their practical applications. The topics covered include AI search algorithms, Classical machine learning, Deep learning theory and popular networks, Natural Language Processing (NLP) and Reinforcement learning. Numerical examples and lucid explanations give the reader an easy entry into the world of AI and ML.

A propos du livre

À propos de l?auteur

Lyla B. Das is Associate Professor, Department of Electronics and Communication Engineering, National Institute of Technology Calicut (NITC), Kerala. Lyla B. Das graduated in 1981 specializing in Electronics and Communications Engineering from the College of Engineering, Trivandrum, Kerala after which she joined Keltron Controls as Deputy Engineer. She started her teaching career as lecturer in 1985 when she joined NITC (then Regional Engineering College, Calicut), and proceeded to complete her master's degree in digital communications from the same institute.

Over the period of the 37 years of her teaching career, she has taught a wide range of courses for undergraduate and postgraduate students, guided numerous projects and presented research papers in conferences and seminars at both national and international levels. Her areas of interest are AI and ML, Embedded Systems, Microprocessors and Microcontrollers, Digital Systems Design and Computer Architecture.

She started her writing career in 2010 when her book Thex86 Microprocessors was published by Pearson Education. This was followed by 'The Embedded Systems –an Integrated Approach' in 2013 and the second edition of the x86 Microprocessors in 2017.Her next book 'Architecture, Programming and Interfacing of Low Power processors –ARM 7, Cortex-M was published by Cengage Publishers in 2018. This is her fourth book.

Sudhish N. George is Associate Professor, Department of Electronics and Communication Engineering, National Institute of Technology Calicut (NITC), Kerala. Sudhish N George received his B.Tech. degree in Electronics and Communication Engineering from the M. A. College of Engineering (M. G. University), Kothamangalam, Kerala, India, in 2004, M.Tech. degree in Signal processing from the College of Engineering Trivandrum (Kerala University) in 2007, and Ph.D. in Multimedia security from NITC in 2014. Since 2010, he has been a faculty in the Department His current research interests include Sparse Signal processing and Computer Vision.

Anup Aprem is Assistant Professor at the Department of ECE in National Institute of Technology, Calicut. Prior to this, he was a postdoctoral researcher in the Applied Machine learning group at the University of Oxford. Anup holds a Ph.D. in Electrical and Computer Engineering from the University of British Columbia, Vancouver, Canada, an M.E. in Signal Processing from Indian Institute of Science Bangalore, and B.Tech in Electronics and Communication Engineering from College of Engineering Trivandrum (University of Kerala). Anup's research interests are broadly in Statistical Signal Processing, Stochastic decision making and Bayesian machine learning, with applications to social media, sensor and social networks and multi-agent systems.

Détails de l'édition

• Éditeur: TechSar Pvt. Ltd
• Date d'édition: 2023
• Langue: anglais
• ISBN 10: 9390620090
• ISBN 13: 9789390620098
• Reliure: Broché
• Nombre de pages: 580
• Coordonnées du fabricant: non disponible