Artificial Intelligence and Machine Learning

Prof. Ajmera Rajesh, Dr. J. Latha

Indexed In: Google scholar

Release Date: 22/06/2024 | Copyright:© 2024 | Pages: 400

DOI: 10.71443/9788197282164

ISBN10: 8197282161 | ISBN13: 9788197282164

Hardcover:$400

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This book offers a comprehensive exploration of Artificial Intelligence (AI), from its foundational concepts to advanced applications across various fields. It begins with an introduction to AI's history, evolution, and key concepts, followed by an in-depth analysis of intelligent agents, problem-solving techniques, and machine learning algorithms. The book delves into data preprocessing, supervised and unsupervised learning, ensemble methods, neural networks, deep learning, and reinforcement learning. It also covers AI applications in Natural Language Processing, Computer Vision, Healthcare, Finance, and Autonomous Systems, highlighting their impact and potential. Each chapter provides practical insights, ethical considerations, and future directions, making this book an essential resource for learners, scholars, and practitioners aiming to harness AI's transformative power in their respective domains. Whether reader are new to AI or seeking to deepen your understanding, this book equips with the knowledge and tools to navigate the rapidly evolving AI landscape.

This book provides a comprehensive exploration of artificial intelligence (AI), covering its history, evolution, and key concepts, while delving into advanced topics such as intelligent agents, machine learning, neural networks, and deep learning. It examines AI's applications across various industries, including healthcare, finance, natural language processing, computer vision, and autonomous systems. The book also addresses the challenges, limitations, and ethical considerations in AI development and implementation. With in-depth analysis of problem-solving techniques, ensemble methods, reinforcement learning, and AI's role in emerging technologies, this book is an essential resource for learners, scholars, and practitioners seeking to comprehend and implement AI across various disciplines.

Table Of Contents

Detailed Table Of Contents


Chapter 1

Introduction to Artificial Intelligence: History, Evolution, and Key Concepts

Dhivya S, Manimegalai R

(Pages:31)

Chapter 2

Intelligent Agents and Environments: Foundations of AI and Interactions with the Physical World

Santosh Kumar Sahu

(Pages:41)

Chapter 3

Advanced Problem-Solving Techniques and Heuristic Search Algorithms in AI

G. Venkatakotireddy

(Pages:49)

Chapter 4

Introduction to Machine Learning: Fundamentals, Techniques, and Applications

B. Suresh Kumar

(Pages:40)

Chapter 5

Comprehensive Data Preprocessing and Feature Engineering for Optimized Machine Learning Models

Rama Nandan Tripathi, Dileep Kumar

(Pages:37)

Chapter 6

Detailed Study of Supervised Learning Algorithms and Their Applications in Real-World Scenarios

S. Praveena

(Pages:38)

Chapter 7

In-Depth Exploration of Unsupervised Learning Algorithms and Techniques for Pattern Discovery

P. Prasant

(Pages:38)

Chapter 8

Ensemble Methods in Machine Learning: Boosting, Bagging, and Stacking for Enhanced Model Performance

Supriya Devi

(Pages:44)

Chapter 9

Neural Networks and Deep Learning Architectures: From Basics to Advanced Implementations

J. Latha

(Pages:41)

Chapter 10

Reinforcement Learning: Algorithms, Techniques, and Applications in Complex Decision-Making

Kavita Srivastava, Brijesh Kumar Bhardwaj

(Pages:41)

Chapter 11

AI in Natural Language Processing: Techniques, Challenges, and Applications in Text and Speech Analysis

Harshit Singh, Kadir Ali

(Pages:37)

Chapter 12

AI in Computer Vision: Image Processing, Object Detection, and Recognition Techniques

J. Latha

(Pages:39)

Chapter 13

Applications of AI in Healthcare: Diagnostics, Treatment Planning, and Predictive Analytics

Ashish Verma

(Pages:35)

Chapter 14

AI in Finance: Algorithmic Trading, Risk Management, and Financial Forecasting

Santosh Gopal Nagpure

(Pages:33)

Chapter 15

AI in Autonomous Systems: Robotics, Self-Driving Cars, and Intelligent Control Systems

Chinnahajisagari Mohammad Akram

(Pages:32)

Chapter 16

Implementing Transfer Learning and Domain Adaptation in IoT Analytics

Poovendran Alagarsundaram, Surendar Rama Sitaraman, Kalyan Gattupalli, Faheem khan

(Pages:29)


Contributions


Ajmera Rajesh completed his B. Tech (ECE) from KITS-Warangal and M.Tech.(CSE) from JNTU-Hyderabad. Currently he is working as an Assistant Professor in the Department of Computer Science at University Arts and Science College Kakatiya University-Warangal Telangana, India. He has published 8 papers in various national and international peer reviewed journals. He has 15 years of teaching experience. He taught several courses to UG and PG students and guided several UG and PG projects. He is working as reviewer for various peer- reviewed reputed journals. 

Dr J. Latha pursed her BE(EEE) & ME (Applied Electronics) in Government College of Technology Coimbatore under Bharathiyar university and her phd in Anna University chennai. She was working as an assistant professor in EEE department faculty of engineering avinashilingam deemed university, coimbatore. She has attended conferences, faculty development programs and has published papers in conferences/journals. At present she is working in electrical power engineering department, university of technology &applied science, shinas sultanate of oman.her area of interest is electrical principles,electrical machines,control systems ,artificial intelligence, neural network digital image processing.


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