Technology is moving at an exponential pace in this era of computational intelligence. Machine learning has emerged as one of the most promising tools used to challenge and think beyond current limitations. This handbook will provide readers with a leading edge to improving their products and processes through optimal and smarter machine learning techniques.

This handbook focuses on new machine learning developments that can lead to newly developed applications. It uses a predictive and futuristic approach, which makes machine learning a promising tool for processes and sustainable solutions. It also promotes newer algorithms that are more efficient and reliable for new dimensions in discovering other applications, and then goes on to discuss the potential in making better use of machines in order to ensure optimal prediction, execution, and decision-making.

Individuals looking for machine learning-based knowledge will find interest in this handbook. The readership ranges from undergraduate students of engineering and allied courses to researchers, professionals, and application designers.

chapter 6|17 pages

Massive Data Classification of Brain Tumors Using DNN

Opportunity in Medical Healthcare 4.0 through Sensors

chapter 8|15 pages

Lung Cancer Risk Stratification Using ML and AI on Sensor-Based IoT

An Increasing Technological Trend for Health of Humanity

chapter 11|25 pages

Artificial Neural Networks

A Comprehensive Review

chapter 14|16 pages

Active Learning from an Imbalanced Dataset

A Study Conducted on the Depression, Anxiety, and Stress Dataset