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INNOVATIONS IN MACHINE LEARNING
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INNOVATIONS IN MACHINE LEARNING

Pencil Bitz Publishing

INNOVATIONS IN MACHINE LEARNING

Techniques and Trends

Available for Pre-order Amazon & Flipkart Promotion Call for Chapters Open

Lead Editor

Dr. R. Pari

Associate Editor

Dr. D. Prabakar

Section Editor

Dr. Tabassum Nahid Sultana

Contributing Editor

Asra Fatima

About This Book

This essential volume brings together the latest research from leading experts in Computer Science and Engineering. It details pioneering algorithms, enhanced classification accuracy methods, and emerging trends in Wireless Sensor Networks, IoT, Information Security, and Artificial Intelligence, providing a critical resource for advanced students and seasoned professionals.

Book Specifications

Release Date

Q4 2025

Features

161 Pages, B&W/Color

ISBN

978-93-48556-35-6

Pre-order Now Download Prospectus

Book Details

Call for Book Chapters

We are currently accepting chapter submissions for this upcoming publication. Contribute to this cutting-edge volume on machine learning innovations.

For submission inquiries, contact:

Harini: +91 9629476711

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Table of Contents: Innovations in Machine Learning: Techniques and Trends

1. Revolutionizing Medical Diagnostics & Prognostics through Deep Learning Page 01

Authors: Padmaja C

2. Predictive Modelling & Intelligent Decision Support in Oncology Page 09

Authors: Dr. Shaik Basheera

3. Personalized Healthcare via Federated Machine Learning Page 15

Authors:Paladi Vishalini

4. ML for Financial Forecasting and Risk Management Page 21

Authors:Rajeswary Nair, Lekshmipriya Vijayan

5. Customer Behaviour & Marketing with Explainable AI Page 27

Authors: Dr. B. Lakshma Reddy, Dr. Sreenivasa Murthy V, Dr. Mage Usha U

6. Fraud Detection in E-Commerce & Digital Banking Page 33

Authors: Dr. Chamundeshwari. G, P. Vinod Kumar

7. IoT Smart Farming: Crop Yield, Soil Monitoring, & Precision Agri. Page 40

Authors:Dr. Kakade Sandeep Kishanrao, Honrao Sachin Babanrao, Dr. Deshpande Asmita Sumant, Prof. Shrishail Sidram Patil

8. ML in Climate Forecasting & Environmental Monitoring Page 50

Authors: Mr. E. Sivarajan

9. Reinforcement Learning in Autonomous Vehicles Page 57

Authors:Mani G

10. IoT Meets ML: Smart Homes & Urban Analytics Page 63

Authors: K. S. R. Rajeswara Rao

11. NLP for Multilingual Retrieval & Sentiment Analysis Page 67

Authors: Dr. R. Dhivya

12. Conversational AI: ML Chatbots in Business & Education Page 75

Authors: Santhi P

13. Adversarial ML for Cybersecurity Defense Page 82

Authors:Mrs. S. Vanitha, Mrs. K. Prabha

14. Ethical ML: Bias, Fairness, and Explainability in Practice Page 103

Authors: Mrs. Nancy Chitra Thilaga N

15. Big Data Machine Learning: Leveraging AI, Big Data, and Cloud Computing for Real-World Impact Page 113

Authors: Dr. M. Ramesh Kumar, Ms. N. Logeshwari, J. Ruby Elizabeth, A. Harini

16. Machine Learning Frontiers: Integrative Techniques, Scalable Systems, and Industry-Driven Use Cases Page 121

Authors: U. L. Sindhu, Mrs. M. Mahabooba, Anju P, Sruthi P S

17. Hybrid AI Models for Dark Web Intelligence Gathering: Deep Learning, Behavioural Analysis & Scalable Cybercrime Detection Page 129

Authors: Dr. E. Kavitha, Mrs. Divyamani M K

18. Machine Learning Frontiers in the Dark Web: Agent-Based Models, Embeddings, and Real-Time Illicit Activity Recognition Page 136

Authors: Mrs K. Prabha, Mrs. S. Vanitha

19. Advancements in Machine Learning for Cybersecurity: Cutting-Edge Techniques, Emerging Trends, and Future Directions in AI-Driven Threat Detection and Prevention Page 142

Authors: D. Usha Rani, S. Habeeb Mohamed Sathak Amina, R. Sudha Abirami, K. Annsheela

20. Machine Learning Innovations in Cybersecurity: Novel Approaches, Group Learning Approaches, and Adaptive Defense Mechanisms Against Evolving Cyber Threats Page 149

Authors:Dr. C. P. Thamil Selvi, Priya B, C. Sandhiya, D. Sujeetha

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