{"product_id":"machine-learning-and-data-science-in-the-power-generation-industry-best-practices-tools-and-case-studies","title":"Machine Learning and Data Science in the Power Generation Industry: Best Practices, Tools, and Case Studies","description":"\u003cp\u003e\u003c\/p\u003e\u003cblockquote\u003e\n\u003cbr\u003eMachine Learning and Data Science in the Power Generation Industry explores current best practices and quantifies the value-add in developing data-oriented computational programs, with a particular focus on real-world case studies. It provides realistic pathways for organizations seeking to develop machine learning methods, discussing data selection and curation, staffing, and organizational implementation. \u003c\/blockquote\u003e\u003cp\u003e                                                            \u003cstrong\u003eFormat\u003c\/strong\u003e: Paperback \/ softback\u003cbr\u003e                              \u003cstrong\u003eLength\u003c\/strong\u003e: 274 pages\u003cbr\u003e                              \u003cstrong\u003ePublication date\u003c\/strong\u003e: 18 January 2021\u003cbr\u003e                              \u003cstrong\u003ePublisher\u003c\/strong\u003e: Elsevier Science Publishing Co Inc\u003cbr\u003e                          \u003c\/p\u003e \u003cp\u003e\u003cbr\u003eMachine Learning and Data Science in the Power Generation Industry delves into cutting-edge practices and quantifies the substantial value-add in creating data-driven computational programs within the power sector. With a keen emphasis on carefully selected real-world case studies, this comprehensive resource offers a roadmap for organizations seeking to harness the power of machine learning. It explores essential aspects such as data selection and curation, as well as organizational implementation, including staffing and ongoing operationalization. The book articulates a wealth of case study-driven best practices, encompassing renewable energy sources, the smart grid, and the intricacies of spot markets, as well as forecasting. By leveraging machine learning and data science, the power generation industry can unlock new opportunities for efficiency, sustainability, and profitability, paving the way for a greener and more resilient future.\u003cbr\u003e\u003c\/p\u003e\u003cp\u003eMachine Learning and Data Science in the Power Generation Industry explores current best practices and quantifies the value-add in developing data-oriented computational programs in the power industry, with a particular focus on thoughtfully chosen real-world case studies.\u003c\/p\u003e\u003cbr\u003eIt provides a set of realistic pathways for organizations seeking to develop machine learning methods, with a discussion on data selection and curation as well as organizational implementation in terms of staffing and continuing operationalization. It articulates a body of case study-driven best practices, including renewable energy sources, the smart grid, and the finances around spot markets, and forecasting.\u003cbr\u003e\u003cbr\u003eBy leveraging machine learning and data science, the power generation industry can unlock new opportunities for efficiency, sustainability, and profitability, paving the way for a greener and more resilient future.\u003cp\u003e                            \u003cstrong\u003eWeight\u003c\/strong\u003e: 582g                            \u003cbr\u003e\u003cstrong\u003eDimension\u003c\/strong\u003e: 193 x 235 x 17 (mm)                            \u003cbr\u003e\u003cstrong\u003eISBN-13\u003c\/strong\u003e: 9780128197424                                                      \u003c\/p\u003e","brand":"Shulph Ink","offers":[{"title":"Paperback \/ softback","offer_id":44096397574394,"sku":"9780128197424","price":96.39,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0522\/4297\/2845\/products\/1c62ccfff26cff970aa9b28a7992b999.jpg?v=1622902331","url":"https:\/\/shulphink.com\/products\/machine-learning-and-data-science-in-the-power-generation-industry-best-practices-tools-and-case-studies","provider":"Shulph Ink","version":"1.0","type":"link"}