Integration of various processes such as identifying, sensing, networking, and computation.
Published in Chapter:
Convergence of AI, ML, and DL for Enabling Smart Intelligence: Artificial Intelligence, Machine Learning, Deep Learning, Internet of Things
Revathi Rajendran (SRM Valliammai Engineering College, India), Arthi Kalidasan (SRM Valliammai Engineering College, India), and Chidhambara Rajan B. (SRM Valliammai Engineering College, India)
Copyright: © 2021
|Pages: 16
DOI: 10.4018/978-1-7998-3111-2.ch011
Abstract
The evolution of digital era and improvements in technology have enabled the growth of a number of devices and web applications leading to the unprecedented generation of huge data on a day-to-day basis from many applications such as industrial automation, social networking cites, healthcare units, smart grids, etc. Artificial intelligence acts as a viable solution for the efficient collection and analyses of the heterogeneous data in large volumes with reduced human effort at low time. Machine learning and deep learning subspaces of artificial intelligence are used for the achievement of smart intelligence in machines to make them intelligent based on learning from experience automatically. Machine learning and deep learning have become two of the most trending, groundbreaking technologies that enable autonomous operations and provide decision making support for data processing systems. The chapter investigates the importance of machine learning and deep learning algorithms in instilling intelligence and providing an overview of machine learning, deep learning platforms.