Mire Archana - Advanced Analytics and Deep Learning Models

Scrivener Publishing
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Beverly, MA 01915-6106

Next-Generation Computing and Communication Engineering

Series Editors: Dr. G. R. Kanagachidambaresan and Dr. Kolla Bhanu Prakash

Developments in artificial intelligence are made more challenging because the involvement of multi-domain technology creates new problems for researchers. Therefore, in order to help meet the challenge, this book series concentrates on next generation computing and communication methodologies involving smart and ambient environment design. It is an effective publishing platform for monographs, handbooks, and edited volumes on Industry 4.0, agriculture, smart city development, new computing and communication paradigms. Although the series mainly focuses on design, it also addresses analytics and investigation of industry-related real-time problems.

Publishers at Scrivener
Martin Scrivener ()
Phillip Carmical ()

Edited by

Archana Mire

Computer Engineering Department, Terna Engineering College, Navi Mumbai, India

Shaveta Malik

Computer Engineering Department, Terna Engineering College, Nerul, India

and

Amit Kumar Tyagi

Vellore Institute of Technology (VIT), Chennai Campus, India

This edition first published 2022 by John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, USA and Scrivener Publishing LLC, 100 Cummings Center, Suite 541J, Beverly, MA 01915, USA
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Library of Congress Cataloging-in-Publication Data

ISBN 978-1-119-79175-1

Cover image: Pixabay.Com
Cover design by Russell Richardson

Set in size of 11pt and Minion Pro by Manila Typesetting Company, Makati, Philippines

Printed in the USA

10 9 8 7 6 5 4 3 2 1

Advanced analytics is a mixture of machine learning, artificial intelligence, graphs, text mining, data mining, semantic analysis. It is an approach to data analysis. Beyond the traditional business intelligence, it is a semi and autonomous analysis of data by using different techniques and tools. However, deep learning and data analysis both are the high centres of data science. Almost all the private and public organizations collect heavy amounts of data, i.e., domain specific data. Many small/large companies are exploring large amounts of data for existing and future technology. Deep learning is also exploring large amounts of unsupervised data.

In fact, it is a key benefit of big data. It is also effective for big data. Moreover, it is collecting an unlabelled and uncategorized raw data. There are some challenges also in big data related to the extraction complex patterns from the large amount of data, retrieving of fast information, tagging of data etc, deep learning can be used to deal these kinds of problems or challenges.

The purpose of this book is to help teachers to instruct the concepts of analytics in deep learning and how big data technologies are managing massive amounts of data with the help of Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL) etc. In this book one will find the utility and challenges of big data. Those who are keen to learn the different models of deep learning, the connection between AI, ML and DL will definitely find this book as a great source of knowledge.

This book contains chapters on artificial intelligence, machine learning, deep learning and their uses in many useful sectors like stock market prediction, recommendation system for better service selection, ehealthcare, telemedicine, transportation. In last few interesting chapter like innovations or issue or future opportunities with fog computing/cloud computing or artificial intelligence are being discussed in this work for future readers/researchers.

Hence, this book will be convenient to the undergraduate and graduate students planning their careers in either industry or research. This will also serve as a great source of learning to software engineers who are beginners in the field of advanced analytics in deep learning.

Dr. Archana Mire
Dr. Shaveta Malik
Dr. Amit Kumar Tyagi
January 2022

Khushboo Kuddus

School of Humanities (English), KIIT Deemed to be University, Bhubaneswar, Odisha, India

Abstract

Fourth Industrial Revolution which features rapid expansion of technology and digital application is influencing almost all spheres of our lives. Artificial Intelligence (AI) has made an impact on the way we live and work, that is, from floor cleaning to instructing Alexa. AI has a great potential in the field of education. AI in education is an emerging field in educational technology. It has an enormous potential of providing digitalized and completely personalized learning to each learner. However, the idea of using AI in education is actually intimidating educators because there is a lot of misconception and misunderstanding regarding the use of AI in education. It is mainly because the educators are unaware of the pedagogical implication of it in education in general and language learning in particular. It is also because of the lack of critical reviews of the pedagogical implications and new approaches in adopting AI in education. Therefore, the present study attempts to explore how AI can be used to enhance language learning experiences. It discusses the tools that can be used to teach English effectively. It further aims to explain how AI can be used to foster learners autonomy. It essentially envisions AI embedded learning in classrooms to enhance English language teaching learning experience and assist the teachers teach their lessons effectively. The findings bring into light some practical and innovative ways, AI can be integrated in ELT classroom to enhance the language teaching learning experience. It focuses on teaching pronunciation and increasing fluency by mimicking the sound pattern and using speech recognition and speech editing features. Moreover, it also highlights the personal approach to language learning by using Chatbot which provides text-to-speech and speech-to-text conversion, using technology to transcribe speech in order to check the pronunciation, translate speech, and practicing conversation by using voice command like Google Assistant. Hence, the paper examines the potential application of AI in education and language learning in particular. Further, it explores the possibilities of implication of AI in classrooms adopting new learning approaches and pedagogical modifications.