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<p>Preface xvii</p> <p><b>Part 1: Natural Language Processing (NLP) Applications 1</b></p> <p>1 A Comprehensive Analysis of Various Tokenization Techniques and Sequence-to-Sequence Model in Natural Language Processing 3<br /><i>Kuldeep Vayadande, Ashutosh M. Kulkarni, Gitanjali Bhimrao Yadav, R. Kumar and Aparna R. Sawant</i></p> <p>2 A Review on Text Analysis Using NLP 13<br /><i>Kuldeep Vayadande, Preeti A. Bailke, Lokesh Sheshrao Khedekar, R. Kumar and Varsha R. Dange</i></p> <p>3 Text Generation & Classification in NLP: A Review 25<br /><i>Kuldeep Vayadande, Dattatray Raghunath Kale, Jagannath Nalavade, R. Kumar and Hanmant D. Magar</i></p> <p>4 Book Genre Prediction Using NLP: A Review 37<br /><i>Kuldeep Vayadande, Preeti Bailke, Ashutosh M. Kulkarni, R. Kumar and Ajit B. Patil</i></p> <p>5 Mood Detection Using Tokenization: A Review 47<br /><i>Kuldeep Vayadande, Preeti A. Bailke, Lokesh Sheshrao Khedekar, R. Kumar and Varsha R. Dange</i></p> <p>6 Converting Pseudo Code to Code: A Review 57<br /><i>Kuldeep Vayadande, Preeti A. Bailke, Anita Bapu Dombale, Varsha R. Dange and Ashutosh M. Kulkarni</i></p> <p><b>Part 2: Machine Learning Applications in Specific Domains 69</b></p> <p>7 Evaluating the Readability of English Language Using Machine Learning Models 71<br /><i>Shiplu Das, Abhishikta Bhattacharjee, Gargi Chakraborty and Debarun Joardar</i></p> <p>8 Machine Learning in Maximizing Cotton Yield with Special Reference to Fertilizer Selection 89<br /><i>G. Hannah Grace and Nivetha Martin</i></p> <p>9 Machine Learning Approaches to Catalysis 101<br /><i>Sachidananda Nayak and Selvakumar Karuthapandi</i></p> <p>10 Classification of Livestock Diseases Using Machine Learning Algorithms 127<br /><i>G. Hannah Grace, Nivetha Martin, I. Pradeepa and N. Angel</i></p> <p>11 Image Enhancement Techniques to Modify an Image with Machine Learning Application 139<br /><i>Shiplu Das, Sohini Sen, Debarun Joardar and Gargi Chakraborty</i></p> <p>12 Software Engineering in Machine Learning Applications: A Comprehensive Study 159<br /><i>Kuldeep Vayadande, Komal Sunil Munde, Amol A. Bhosle, Aparna R. Sawant and Ashutosh M. Kulkarni</i></p> <p>13 Machine Learning Applications in Battery Management System 173<br /><i>Ponnaganti Chandana and Ameet Chavan</i></p> <p>14 ML Applications in Healthcare 201<br /><i>Farooq Shaik, Rajesh Yelchurri, Noman Aasif Gudur and Jatindra Kumar Dash</i></p> <p>15 Enhancing Resource Management in Precision Farming through AI-Based Irrigation Optimization 221<br /><i>Salina Adinarayana, Matha Govinda Raju, Durga Prasad Srirangam, Devee Siva Prasad, Munaganuri Ravi Kumar and Sai babu veesam</i></p> <p>16 An In-Depth Review on Machine Learning Infusion in an Agricultural Production System 253<br /><i>Sarthak Dash, Sugyanta Priyadarshini and Sukanya Priyadarshini</i></p> <p><b>Part 3: Artificial Intelligence and Optimization Techniques 271</b></p> <p>17 Reinforcement Learning Approach in Supply Chain Management: A Review 273<br /><i>Rajkanwar Singh, Pratik Mandal and Sukanta Nayak</i></p> <p>18 Alternate Approach to Solve Differential Equations Using Artificial Neural Network with Optimization Technique 303<br /><i>Ramanan R., Sukanta Nayak and Arun Kumar Gupta</i></p> <p>19 GPT-3- and DALL-E-Powered Applications: A Complete Survey 329<br /><i>Kuldeep Vayadande, Chaitanya B. Pednekar, Priya Anup Khune, Vinay Sudhir Prabhavalkar and Varsha R. Dange</i></p> <p>20 New Variation of Exam Scheduling Problem Using Graph Coloring 343<br /><i>Angshu Kumar Sinha, Soumyadip Laha, Debarghya Adhikari, Anjan Koner and Neha Deora</i></p> <p><b>Part 4: Emerging Topics in Machine Learning 353</b></p> <p>21 A Comparative Study of Different Techniques of Text-to-SQL Query Converter 355<br /><i>Kuldeep Vayadande, Preeti A. Bailke, Vikas Janu Nandeshwar, R. Kumar and Varsha R. Dange</i></p> <p>22 Trust-Based Leader Election in Flying Ad-Hoc Network 367<br /><i>Joydeep Kundu, Sahabul Alam and Sukanta Oraw</i></p> <p>23 A Survey on Domain of Application of Recommender System 375<br /><i>Sudipto Dhar</i></p> <p>24 New Approach on M/M/c/K Queueing Models via Single Valued Linguistic Neutrosophic Numbers and Perceptionization Using a Non-Linear Programming Technique 383<br /><i>Antony Crispin Sweety C. and Vennila B.</i></p> <p>25 The Rise of AI-Generated News Videos: A Detailed Review 423<br /><i>Kuldeep Vayadande, Mustansir Bohri, Mohit Chawala, Ashutosh M. Kulkarni and Asif Mursal</i></p> <p>References 449</p> <p>Index 453</p>

<p><b>Arindam Dey, PhD,</b> is an associate professor at the School of Computer Science, VIT-AP University, India. He has published more than 50 research articles in national and international peer-reviewed journals. Dr. Dey has 14 years of teaching and research experience in the areas of optimization and genetic algorithms. <p><b>Sukanta Nayak, PhD,</b> is an assistant professor in the Department of Mathematics, School of Advanced Sciences (SAS) at VIT-AP University, Amaravati, Andhra Pradesh, India. He completed his doctoral research at NIT Rourkela, has authored three books, and published numerous research articles in international journals. <p><b>Ranjan Kumar, PhD,</b> is an assistant professor in the Department of Mathematics, School of Advanced Sciences (SAS) at VIT-AP University, Amaravati, Andhra Pradesh, India. He has numerous peer-reviewed research articles to his name and is the recipient of numerous awards and titles including an Honorary Professorship from Cypress International Institute University, Texas, USA. <p><b>Sachi Nandan Mohanty, PhD,</b> is in the School of Computer Science and Engineering (SCOPE) at VIT-AP University, Amaravati, Andhra, Pradesh, India. He has edited 25 books and published 60 international journals of international repute. His research areas include data mining, big data analysis, cognitive science, fuzzy decision-making, brain-computer interface, cognition, and computational intelligence. In 2015, he was awarded the first prize of the Best Thesis Award by the Computer Society of India.

<p><b>Provides a comprehensive understanding of the latest advancements and practical applications of machine learning techniques.</b> <p>Machine learning (ML), a branch of artificial intelligence, has gained tremendous momentum in recent years, revolutionizing the way we analyze data, make predictions, and solve complex problems. As researchers and practitioners in the field, the editors of this book recognize the importance of disseminating knowledge and fostering collaboration to further advance this dynamic discipline. “How Machine Learning is Innovating Today’s World” is a timely book and presents a diverse collection of 25 chapters that delve into the remarkable ways that ML is transforming various fields and industries. <p>It provides a comprehensive understanding of the practical applications of ML techniques. The wide range of topics include: <p>An analysis of various tokenization techniques and the sequence-to-sequence model in natural language processing • explores the evaluation of English language readability using ML models • a detailed study of text analysis for information retrieval through natural language processing • the application of reinforcement learning approaches to supply chain management • the performance analysis of converting algorithms to source code using natural language processing in Java • presents an alternate approach to solving differential equations utilizing artificial neural networks with optimization techniques • a comparative study of different techniques of text-to-SQL query conversion • the classification of livestock diseases using ML algorithms • ML in image enhancement techniques • the efficient leader selection for inter-cluster flying ad-hoc networks • a comprehensive survey of applications powered by GPT-3 and DALL-E • recommender systems’ domain of application • reviews mood detection, emoji generation, and classification using tokenization and CNN • variations of the exam scheduling problem using graph coloring • the intersection of software engineering and machine learning applications • explores ML strategies for indeterminate information systems in complex bipolar neutrosophic environments • ML applications in healthcare, in battery management systems, and the rise of AI-generated news videos • how to enhance resource management in precision farming through AI-based irrigation optimization. <p><b>Audience</b> <p>The book will be extremely useful to professionals, post-graduate research scholars, policymakers, corporate managers, and anyone with technical interests looking to understand how machine learning and artificial intelligence can benefit their work.

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