The publication is attempted to address emerging trends in machine
learning applications. Recent trends in information identification have
identified huge scope in applying machine learning techniques for
gaining meaningful insights. Random growth of unstructured data poses
new research challenges to handle this huge source of information.
Efficient designing of machine learning techniques is the need of the
hour. Recent literature in machine learning has emphasized on single
technique of information identification. Huge scope exists in developing
hybrid machine learning models with reduced computational complexity for
enhanced accuracy of information identification. This book will focus on
techniques to reduce feature dimension for designing light weight
techniques for real time identification and decision fusion. Key
Findings of the book will be the use of machine learning in daily lives
and the applications of it to improve livelihood. However, it will not
be able to cover the entire domain in machine learning in its limited
scope. This book is going to benefit the research scholars,
entrepreneurs and interdisciplinary approaches to find new ways of
applications in machine learning and thus will have novel research
contributions. The lightweight techniques can be well used in real time
which will add value to practice.
