Foundations of Data Science for Engineering Problem Solving (eBook)
eBook Download:
PDF
2021
|
1st ed. 2022
XIV, 117 Seiten
Springer Singapore (Verlag)
978-981-16-5160-1 (ISBN)
XIV, 117 Seiten
Springer Singapore (Verlag)
978-981-16-5160-1 (ISBN)
This book is one-stop shop which offers essential information one must know and can implement in real-time business expansions to solve engineering problems in various disciplines. It will also help us to make future predictions and decisions using AI algorithms for engineering problems. Machine learning and optimizing techniques provide strong insights into novice users. In the era of big data, there is a need to deal with data science problems in multidisciplinary perspective. In the real world, data comes from various use cases, and there is a need of source specific data science models. Information is drawn from various platforms, channels, and sectors including web-based media, online business locales, medical services studies, and Internet. To understand the trends in the market, data science can take us through various scenarios. It takes help of artificial intelligence and machine learning techniques to design and optimize the algorithms. Big data modelling and visualization techniques of collected data play a vital role in the field of data science. This book targets the researchers from areas of artificial intelligence, machine learning, data science and big data analytics to look for new techniques in business analytics and applications of artificial intelligence in recent businesses.
Dr. Priya Dudhale Pise has 16 years of experience. She has done her Ph.D. in Cloud Computing and Big Data Security from JJTU, Rajasthan, with tittle 'Sensitive Data Sharing Securely in Big Data for Privacy Preservation on Recent Operating Systems'-Ph.D. awarded on November 25, 2018. She has pursued her B.E. in Information Technology from MIT Kothrud (SPPU) and Master's degree M.E. in Computer Engineering from MIT Alandi (SPPU) in 2012. She won 'Best Technical Paper Award' for 2 national and 1 international conferences. She has bagged 'Backbone of Indian Technical Academics' in December 2018. She is an author of a book on 'Fundamentals of Data Structures.' She also has published one national and one international patent on her name. She recently has presented her research article in ACM International Conference held in University of Cambridge, London, UK. She has presented 50+ papers in national and international conferences and journals. She is an editorial member of one of the renowned journal.
This book is one-stop shop which offers essential information one must know and can implement in real-time business expansions to solve engineering problems in various disciplines. It will also help us to make future predictions and decisions using AI algorithms for engineering problems. Machine learning and optimizing techniques provide strong insights into novice users. In the era of big data, there is a need to deal with data science problems in multidisciplinary perspective. In the real world, data comes from various use cases, and there is a need of source specific data science models. Information is drawn from various platforms, channels, and sectors including web-based media, online business locales, medical services studies, and Internet. To understand the trends in the market, data science can take us through various scenarios. It takes help of artificial intelligence and machine learning techniques to design and optimize the algorithms. Big data modelling and visualization techniques of collected data play a vital role in the field of data science. This book targets the researchers from areas of artificial intelligence, machine learning, data science and big data analytics to look for new techniques in business analytics and applications of artificial intelligence in recent businesses.
Dr. Parikshit N. Mahalle obtained B.E. degree in Computer Engineering from Amravati University, M.E. degree from SPPU, Pune, and Ph.D. in specialization in Wireless Communication from Aalborg University, Denmark. He was Postdoctoral Researcher at CMI, Aalborg University, Copenhagen. Currently, he is working as Professor and Head in the Department of Artificial intelligence and Data Science at Vishwakarma Institute of Information Technology and is recognized as Ph.D. Guide of SSPU Pune. He has 20 years of teaching and research experience. He is on Research and Recognition Committee at several universities. He is Senior Member of IEEE and ACM and Life member of CSI and ISTE. He is Reviewer and Editor of ACM, Springer, Elsevier Journals and Member of Editorial Review Board for IGI Global. He has published 150+ publications with 1242 citations and H index 14. He edited 5 books and authored 13 books and 7 patents to his credit. He has published a book on Data Analytics for COVID-19 Outbreak. He has delivered 100+ lectures at national and international levels on IoT, big data and digitization. He had worked as BOS-Chairman for Information Technology and working as Member-BOS Computer Engineering, SPPU, and several other institutions also. He received 'Best Faculty Award' by Sinhgad Institutes and Cognizant Technologies Solutions.
Dr. Gitanjali R. Shinde has overall 12 years of experience and is presently working as SPPU-approved Assistant Professor in the Department of Computer Engineering, Smt. Kashibai Navale College of Engineering, Pune-41. She has done Ph.D. in Wireless Communication from CMI, Aalborg University, Copenhagen, Denmark, on Research Problem Statement 'Cluster Framework for Internet of People, Things and Services'-Ph.D. awarded on May 8, 2018. She obtained M.E. (Computer Engineering) degree from University of Pune, Pune, in 2012 and B.E. (Computer Engineering) degree from University of Pune, Pune, in 2006. She has received research funding for project 'lightweight group authentication for IoT' by SPPU, Pune. She has presented research article in World Wireless Research Forum (WWRF) meeting, Beijing, China. She has published 50+ papers in national and international conferences and journals. She is an author of 5+ books with publisher like Springer Nature and CRC Taylor & Francis Group. She is also Editor of books with De Gruyter and Springer Nature Press. She is Reviewer of prominent journal IGI publication and IEEE Transactions.
Ms. Jyoti Yogesh Deshmukh has overall 11 years of experience and is presently working as SPPU-approved Assistant Professor in the Department of Computer Engineering, JSPM's Bhivarabai Sawant Institute of Technology and Research, Wagholi, Pune-412207. She is pursuing her Ph.D. in Cloud Computing and Data Security from JJTU, Rajasthan, on Research Problem Statement 'Message Privacy with Load Balancing Using Attribute-Based Encryption.' She obtained M.E. (Computer Engineering) degree from University of Pune, Pune, in 2015 and B.E. (Information Technology) degree from STES's Smt. Kashibai Navale College of Engineering, Pune-41, in 2006. She has published 10+ papers in national and international conferences and journals.
This book is one-stop shop which offers essential information one must know and can implement in real-time business expansions to solve engineering problems in various disciplines. It will also help us to make future predictions and decisions using AI algorithms for engineering problems. Machine learning and optimizing techniques provide strong insights into novice users. In the era of big data, there is a need to deal with data science problems in multidisciplinary perspective. In the real world, data comes from various use cases, and there is a need of source specific data science models. Information is drawn from various platforms, channels, and sectors including web-based media, online business locales, medical services studies, and Internet. To understand the trends in the market, data science can take us through various scenarios. It takes help of artificial intelligence and machine learning techniques to design and optimize the algorithms. Big data modelling and visualization techniques of collected data play a vital role in the field of data science. This book targets the researchers from areas of artificial intelligence, machine learning, data science and big data analytics to look for new techniques in business analytics and applications of artificial intelligence in recent businesses.
| Erscheint lt. Verlag | 21.8.2021 |
|---|---|
| Reihe/Serie | Studies in Big Data | Studies in Big Data |
| Zusatzinfo | XIV, 117 p. 58 illus., 50 illus. in color. |
| Sprache | englisch |
| Themenwelt | Mathematik / Informatik ► Informatik ► Datenbanken |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Mathematik / Informatik ► Mathematik ► Angewandte Mathematik | |
| Mathematik / Informatik ► Mathematik ► Finanz- / Wirtschaftsmathematik | |
| Technik | |
| Wirtschaft | |
| Schlagworte | Big data modeling • Business Intelligence • data analytics • Engineering Problem Solving • machine learning • optimization algorithms |
| ISBN-10 | 981-16-5160-4 / 9811651604 |
| ISBN-13 | 978-981-16-5160-1 / 9789811651601 |
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