Doing Data Science is a comprehensive compilation of lectures and insights by data scientists, who have hands-on experience working with top firms such as Microsoft, Google, and eBay. With data playing a key role in businesses across all industries, data science is quickly turning into a lucrative career. But with the field being so vast, it becomes difficult to comprehend the basics. This book breaks it down and provides readers with practical insight into the field. This book covers topics such as Logistic regression, Spam filters, Data wrangling, Naive Bayes, Data visualisation, Financial modeling, Statistical interference, Data engineering, Pregel, MapReduce, and Hadoop, Social networks and data journalism, and more. Data scientists have narrated case studies of the projects they have worked on. Readers will learn about new methods and algorithms and the code systems that these scientists have used. Doing Data Science will help statisticians understand the relation between statistics and data science. It is written in a linear manner and thoroughly explains the concepts and how they are built one on top of the other. The authors also write about what the future holds for this discipline. This book even contains suggestions for additional reading material that will help readers gain a better insight.

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