Artificial Intelligence and Machine Learning: Theory and Practice, 1/e
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Artificial Intelligence and Machine Learning: Theory and Practice, 1/e

Author : Lyla B. Das , Sudhish N. George & Anup Aprem
© Year : 2022
ISBN : 9789390620098
Pages : 550
Binding : Paperback
Dimension : 7.2 x 9.5

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  • About the Book
  • Salient Features
  • About the Author

Artificial Intelligence (AI) is a very broad area of knowledge which has percolated into every aspect of human life. What is generally referred to as ';machine learning algorithms' is considered to be a subset of AI because AI is not just machine learning alone. 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).
AI search algorithms which are also very old but very important, are also explained.
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.
The book covers the conceptual, mathematical and numerical analysis of the important 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.
This book is designed for undergraduates, postgraduates and professionals who want to have a firm grip on the fundamental principles of AI and ML.

  • Clear and lucid explanations of concepts with in-depth analysis
  • Numerical examples to ensure  clear understanding
  • Critical evaluation of latest applications
  • Inclusion of coding examples and necessary math
  • Elaborate coverage of Deep Learning Networks such as CNN,RNN and GAN
  • Step by step coverage of NLP  processes and applications
  • Exclusive chapter on Attention mechanisms and Transformers
  • Extensive coverage of Reinforcement Learning algorithms

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 The  x86 Microprocessors was published  by Pearson Education. This was followed by ';The Embedded Systems -an Integrated Approach' in 2013 and the second edition ofThe  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.

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.

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 theDepartment His current research interests include Sparse Signal processing and Computer Vision.

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