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Titlebook: Foundations of Data Science for Engineering Problem Solving; Parikshit Narendra Mahalle,Gitanjali Rahul Shinde, Book 2022 The Editor(s) (i

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書目名稱Foundations of Data Science for Engineering Problem Solving
編輯Parikshit Narendra Mahalle,Gitanjali Rahul Shinde,
視頻videohttp://file.papertrans.cn/347/346939/346939.mp4
概述Provides clear information about need of data science.Emphasizes use context in developing context-aware data science solutions.Discusses various technologies, methodologies, and approaches
叢書名稱Studies in Big Data
圖書封面Titlebook: Foundations of Data Science for Engineering Problem Solving;  Parikshit Narendra Mahalle,Gitanjali Rahul Shinde, Book 2022 The Editor(s) (i
描述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 analytic
出版日期Book 2022
關(guān)鍵詞Machine Learning; Engineering Problem Solving; Big Data Modeling; Data Analytics; Business Intelligence;
版次1
doihttps://doi.org/10.1007/978-981-16-5160-1
isbn_softcover978-981-16-5162-5
isbn_ebook978-981-16-5160-1Series ISSN 2197-6503 Series E-ISSN 2197-6511
issn_series 2197-6503
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
The information of publication is updating

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