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dc.contributor.authorIgual, Laura
dc.contributor.authorSeguí, Santi
dc.date.accessioned2020-05-26T08:58:42Z
dc.date.available2020-05-26T08:58:42Z
dc.date.issued2017
dc.identifier.isbn978-3-319-50017-1
dc.identifier.urihttp://ir.mksu.ac.ke/handle/123456780/6308
dc.description.abstractIn this era, where a huge amount of information from different fields is gathered and stored, its analysis and the extraction of value have become one of the most attractive tasks for companies and society in general. The design of solutions for the new questions emerged from data has required multidisciplinary teams. Computer scientists, statisticians, mathematicians, biologists, journalists and sociologists, as well as many others are now working together in order to provide knowledge from data. This new interdisciplinary field is called data science. The pipeline of any data science goes through asking the right questions, gathering data, cleaning data, generating hypothesis, making inferences, visualizing data, assessing solutions, etc.en_US
dc.language.isoen_USen_US
dc.titleIntroduction to Data Scienceen_US
dc.title.alternativeA Python Approach to Concepts, Techniques and Applicationsen_US
dc.typeBooken_US


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