Data Science For Dummies 2nd Edition begins by explaining large data sets and data formats, including sample Python code for manipulating data. The book explains how to work with relational databases and unstructured data, including NoSQL. The book then moves into preparing data for analysis by cleaning it up or "munging" it. From there the book explains data visualization techniques and types of data sets. Part II of the book is all about supervised machine learning, including regression techniques and model validation techniques. Part III explains unsupervised machine learning, including clustering and recommendation engines. Part IV overviews big data processing, including MapReduce, Hadoop, Dremel, Storm, and Spark. The book finishes up with real world applications of data science and how data science fits into organizations.
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Lillian Pierson, P.E. is a data scientist, professional environmental engineer, and leading data science consultant to global leaders in IT, major governmental and non-governmental entities, prestigious media corporations, and not-for-profit technology groups.
A guide book for your journey towards an exciting new data science career
Think you'd like to pursue a career in data science? Let this book be your guide. Data Science For Dummies is for working professionals and students interested in transforming an organization's sea of structured, semi-structured, and unstructured data into actionable business insights. It gets you up-to-speed on what's happening across this broad industry, giving you a head start in turning messy data into meaningful stories that all people in an organization can use.
Inside
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