Multimedia Data Processing And Computing

This book focuses on different applications of multimedia with supervised and unsupervised data engineering in the modern world. It includes AI-based soft computing and machine techniques in the field of medical diagnosis biometrics networking manufacturing data science automation in electronics industries and many more relevant fields. Multimedia Data Processing and Computing provides a complete introduction to machine learning concepts as well as practical guidance on how to use machine learning tools and techniques in real-world data engineering situations. It is divided into three sections. In this book on multimedia data engineering and machine learning the reader will learn how to prepare inputs interpret outputs appraise discoveries and employ algorithmic strategies that are at the heart of successful data mining. The chapters focus on the use of various machine learning algorithms neural net- work algorithms evolutionary techniques fuzzy logic techniques and deep learning techniques through projects so that the reader can easily understand not only the concept of different algorithms but also the real-world implementation of the algorithms using IoT devices. The authors bring together concepts ideas paradigms tools methodologies and strategies that span both supervised and unsupervised engineering with a particular emphasis on multimedia data engineering. The authors also emphasize the need for developing a foundation of machine learning expertise in order to deal with a variety of real-world case studies in a variety of sectors such as biological communication systems healthcare security finance and economics among others. Finally the book also presents real-world case studies from machine learning ecosystems to demonstrate the necessary machine learning skills to become a successful practitioner. The primary users for the book include undergraduate and postgraduate students researchers academicians specialists and practitioners in computer science and engineering.