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.
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