书目名称 | Foundations of Data Science for Engineering Problem Solving | 编辑 | Parikshit Narendra Mahalle,Gitanjali Rahul Shinde, | 视频video | | 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 | 丛书名称 | Studies in Big Data | 图书封面 |  | 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 | 关键词 | Machine Learning; Engineering Problem Solving; Big Data Modeling; Data Analytics; Business Intelligence; | 版次 | 1 | doi | https://doi.org/10.1007/978-981-16-5160-1 | isbn_softcover | 978-981-16-5162-5 | isbn_ebook | 978-981-16-5160-1Series ISSN 2197-6503 Series E-ISSN 2197-6511 | issn_series | 2197-6503 | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor |
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