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zásady používania súborov cookiezásady ochrany osobných údajovParametre
Stav | Nové |
Faktúra | Vystavujem faktúry s DPH |
Jazyk vydania | Angličtina |
Názov | Introduction to Quantum Computing & Machine Learning Technologies |
Autor | Sreedevi, Dr. M. |
Nosič | papierová kniha |
Obal knihy | brožovaná väzba |
Rok vydania | 2022 |
Nakladateľstvo | inne (Draft2Digital L.L.C) |
Opis
Introduction to Quantum Computing Machine Learning Technologies
- Autor: Sreedevi, Dr. M.
- Wydawnictwo: Draft2Digital L.L.C
- Data wydania: 2022-07-21
- Liczba stron: 80
- Wymiary: 21.6 x 0.5 x 29.2
- Język: English: Published; English: Original Language; English
- ISBN: 9798201626808
About the Book: Quantum computing is a sophisticated approach to making parallel calculations, using the physics that governs subatomic particles to replace the more simplistic transistors in today’s computers. Therefore it holds the promise to solve some of our planet's biggest challenges - in the areas of environment, agriculture, health, energy, climate, materials science, and others we haven't encountered yet. For some of these problems, classical computing is increasingly challenged as the size of the system grows. When designed to scale, quantum systems will presumably have some capabilities that exceed our most powerful supercomputers. Machine learning is a branch of artificial intelligence (AI) and computer science which focuses on the use of data and algorithms to imitate the way that humans learn, gradually improving its accuracy. It is undeniably one of the most influential and powerful technologies in today’s world. More importantly, we are far from seeing its full potential. There’s no doubt, it will continue to be making headlines for the foreseeable future. Machine learning is a tool for turning information into knowledge. In the past 50 years, there has been an explosion of data. This mass of data is useless unless we analyze it and find the patterns hidden within. Machine learning techniques are used to automatically find the valuable underlying patterns within complex data that we would otherwise struggle to discover. The hidden patterns and knowledge about a problem can be used to predict future events and perform all kinds of complex decision making. About the Authors: Dr. M. Sreedevi is working as a Professor and HOD in Department of Computer Science and Technology at Madanapalle Institute of Technology and Science (UGC-Autonomous), Madanapalle, Andhra Pradesh, India. She has completed PhD in Network Security from S.V.U.C.E, S. V. University, Tirupati, M.Tech in IT from Punjabi University, Patiala and B.Tech in ECE from S.V.U.C.E, S. V. University, Tirupati. She has published more than 30 research papers in international journals and conferences and organized various international workshops and conferences. Her research interests include Cryptography and Network Security, Blockchain and Machine Learning technologies. Mr. Soumya Ranjan Jena is currently working as an Assistant Professor in Department of Computer Science and Technology at Madanapalle Institute of Technology and Science (UGC-Autonomous), Madanapalle, Andhra Pradesh, India. He has completed M.Tech in IT from Utkal University, Bhubaneswar, Odisha, B.Tech in CSE from BPUT, Odisha and CCNA from CTTC. He has published 3 books, 12 Scopus indexed research papers, 23 WoS indexed research papers, and 5 patents. His research interests include Cloud and Distributed Computing, IoT, Green Computing etc. Dr. Vani Rajasekar is currently working as Assistant Professor in Department of Computer Science and Engineering at Kongu Engineering College, Erode, Tamil Nadu, India. She has completed PhD in Information and Communication Engineering from Anna University, Tamil Nadu, M.Tech in Information and Cyber Warfare from Kongu Engineering College, Erode, Tamil Nadu, India and B.Tech in Information Technology from Kongu Engineering College, Erode, Tamil Nadu, India. She has published more than 40 research papers and book chapters published in various international journals and conferences which are indexed by Scopus, Web of Science and SCI. Her research interests include Cryptography, Network Security, Biometrics and Wireless Networks.
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