MACHINE LEARNING FOR NATURAL LANGUAGE PROCESSING: INSIGHTS INTO TEXT AND SPEECH ANALYSIS

Name: MACHINE LEARNING FOR NATURAL LANGUAGE PROCESSING: INSIGHTS INTO TEXT AND SPEECH ANALYSIS
Rating: 5 (1 reviews)

Mr. Harish Reddy Gantla · Dr. Nancy Arya · Dr. Divyanshu Sinha · Dr. Rakhi Mutha

May 2024 · Xoffencerpublication

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236

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About this ebook

The fourth industrial revolution, according to the World Economic Forum, is about to begin. This will blend the physical and digital worlds in ways we couldn’t imagine a few years ago. Advances in machine learning and AI will help usher in these existing changes. Machine learning is transformative which opens up new scenarios that were simply impossible a few years ago. Profound gaining addresses a significant change in perspective from customary programming improvement models. Instead of having to write explicit top-down instructions for how software should behave, deep learning allows your software to generalize rules of operations. Deep learning models empower the engineers to configure, characterized by the information without the guidelines to compose. Deep learning models are conveyed at scale and creation applications—for example, car, gaming, medical services, and independent vehicles. Deep learning models employ artificial neural networks, which are computer architectures comprising multiple layers of interconnected components. By avoiding data transmission through these connected units, a neural network can learn how to approximate the computations required to transform inputs to outputs. Deep learning models require top-notch information to prepare a brain organization to carry out a particular errand. Contingent upon your expected applications, you might have to get thousands to millions of tests. This chapter takes you on a journey of AI from where it got originated. It does not just involve the evolution of computer science, but it involves several fields say biology, statistics, and probability. Let us start its span from biological neurons; way back in 1871, Joseph von Gerlach proposed the reticulum theory, which asserted that “the nervous system is a single continuous network rather than a network of numerous separate cells.” According to him, our human nervous system is a single system and not a network of discrete cells. Camillo Golgi was able to examine neural tissues in greater detail than ever before, thanks to a chemical reaction he discovered. He concluded that the human nervous system was composed of a single cell and reaffirmed his support for the reticular theory. In 1888, Santiago Ramon y Cajal used Golgi’s method to examine the nervous system and concluded that it is a collection of distinct cells rather than a single cell.

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About the author

Mr. Harish Reddy Gantla is from Hyderabad (Telangana State, India). He is Pursuing Ph.D. from the JNTUH, Hyderabad. He had completed his M.Tech in CSE from the same university. He is having 19 years of experience in teaching and 11 years of experience in Research. He worked as an Assistant Professor in IT Department for 16 Years at SreeNidhi Institute of Science and Technology, Hyderabad and currently working as an Associate Professor in CSE Department and Additional Controller of Examinations at Vignan Institute of Technology and Science. He got a chance as a visiting professor from APPA, and had designed a course on Network Security for them. He was as a resource person for 3 workshops and convener for 4 workshops organized by SNIST under TEQIP. He published a book titled "A handbook on Big Data and Machine Learning". He published 12 patents including 6 design patents with Grants, 6 International journals, 9 International Conferences and 6 National conference papers. His areas of interest include Computer Networks, Cryptography, Big Data IoT and Machine Learning.

Dr. Nancy Arya is an Associate Professor in the Department of Computer Science & Engineering, Faculty of Engineering & Technology at SGT University. Her research areas of interest are Cloud Computing, Wireless Networking and Security, Blockchain and Machine Learning. She has more than 25 quality research papers and 10 patents to her credit. She is a professional member of IEEE. She is the paper reviewer for many international conferences and Journals (SCI and Scopus Indexed). She is the author of three books. She is IBM Certified DB2 Associate and secured 98.94%, the highest score record till April 2009 in India. She is also IBM Certified Deployment Professional Tivoli Directory Server V6.1 and secured 98.90%.

Dr. Divyanshu Sinha, presently Associate Professor in Computer Science Engineering Department MRIIRS Faridabad is a seasoned professional in the realm of technology and education. With over 14 years of experience bridging academia and industry giants like KPMG and Xebia, Dr. Sinha is a certified Machine Learning Practitioner by KPMG, an AI specialist accredited by Andrew Ng's Deeplearning.ai, and holds certifications from Microsoft and Wipro. His expertise spans a multitude of domains including Machine Learning, Data Analytics, and Digital Image Processing, coupled with adept team management skills. Not just confined to the practical world, Dr. Sinha is also a distinguished academician, holding a PhD in Computer Science. His academic journey is enriched with numerous research publications in esteemed international journals indexed in Scopus and SCI. Beyond publications, Dr. Sinha's innovative contributions extend to the patent landscape, with his works granted patents in India, Australia, and Germany. In summary, Dr. Divyanshu Sinha stands as a beacon of knowledge and innovation, blending academic rigor with practical prowess in the everevolving landscape of technology and education.

Dr. Rakhi Mutha is an Associate Professor at Amity University Rajasthan, with over 15 years of teaching experience in computer science at both graduate and postgraduate levels in India and Muscat, Sultanate of Oman. Holding a Ph.D. and M.Tech. in Computer Science and Engineering, she is a prolific researcher with 35+ publications, including books, chapters, and papers in prestigious international journals and conferences. Dr. Mutha's innovative contributions extend to intellectual property rights, with 12 patents published under IPR India, 5 granted patents, 2 UK granted patents, and 2 Canadian copyrights. She is a certified ISTE Trainer for Internet of Things (IOT) and an IBM Certified Academic Associate for DB2. Her expertise is evident in her numerous expert lectures, technical session chairs, and board memberships in reputable international and Scopus-indexed journals. A member of professional societies like CSI, IAENG, and ISTE, Dr. Mutha's research interests encompass Blockchain, Artificial Intelligence, Internet of Things, Big Data, and Cybersecurity, making her a prominent figure in academia and industry.

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