{"product_id":"elements-of-data-science-machine-learning-and-artificial-intelligence-using-r-9783031133381","title":"Elements of Data Science, Machine Learning, and Artificial Intelligence Using R","description":"\u003cp\u003e\u003c\/p\u003e\u003cblockquote\u003e\n\u003cbr\u003eThe textbook provides students with tools to analyze complex data using methods from data science, machine learning, and artificial intelligence, with presentations and implementations in R. It covers computer science, mathematics, statistics, and domain knowledge and teaches computational thinking in a natural way. \u003c\/blockquote\u003e\u003cp\u003e\u003cstrong\u003eFormat\u003c\/strong\u003e: Hardback\u003cbr\u003e\u003cstrong\u003eLength\u003c\/strong\u003e: 575 pages\u003cbr\u003e\u003cstrong\u003ePublication date\u003c\/strong\u003e: 27 June 2023\u003cbr\u003e\u003cstrong\u003ePublisher\u003c\/strong\u003e: Springer International Publishing AG\u003cbr\u003e\u003c\/p\u003e \u003cp\u003e\u003cbr\u003eThe textbook serves as an invaluable resource for students seeking to delve into the realm of complex data analysis, employing a multitude of methods derived from data science, machine learning, and artificial intelligence. Authored by esteemed experts, the book offers a comprehensive presentation of these methodologies, accompanied by practical applications utilizing the widely recognized programming language R. Recognized as the gold standard in data analysis, R provides a seamless platform for exploring and extracting valuable insights from data. Spanning three fundamental components of data science, namely computer science, mathematics, and statistics, the book equips students with a comprehensive understanding of the field. By presenting methods and implementations in R alongside each other, the book enables immediate practical application of the acquired learning concepts. Moreover, it fosters computational thinking in a natural and intuitive manner. The textbook is enriched with a plethora of exercises, case studies, Q\u0026amp;A sections, and illustrative examples, further enhancing the learning experience and reinforcing the theoretical concepts. Whether students are aspiring data scientists, researchers, or professionals seeking to enhance their data analysis skills, this textbook serves as a indispensable guide, providing them with the tools and knowledge necessary to navigate the intricate world of complex data analysis.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWeight\u003c\/strong\u003e: 1222g\u003cbr\u003e\u003cstrong\u003eDimension\u003c\/strong\u003e: 235 x 155 (mm)\u003cbr\u003e\u003cstrong\u003eISBN-13\u003c\/strong\u003e: 9783031133381\u003cbr\u003e \u003cstrong\u003eEdition number\u003c\/strong\u003e: 1st ed. 2023\u003c\/p\u003e","brand":"Frank Emmert-Streib,Salissou Moutari,Matthias Dehmer","offers":[{"title":"Hardback","offer_id":44638741332218,"sku":"9783031133381","price":47.11,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0522\/4297\/2845\/products\/1697212906324_book.jpg?v=1697393450","url":"https:\/\/shulphink.com\/products\/elements-of-data-science-machine-learning-and-artificial-intelligence-using-r-9783031133381","provider":"Shulph Ink","version":"1.0","type":"link"}