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Principles of Data Science. Mathematical techniques and theory to succeed in data-driven industries Sinan Ozdemir

Język publikacji: angielskim
Principles of Data Science. Mathematical techniques and theory to succeed in data-driven industries Sinan Ozdemir - okladka książki

Principles of Data Science. Mathematical techniques and theory to succeed in data-driven industries Sinan Ozdemir - okladka książki

Autor:
Sinan Ozdemir
Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
388
Dostępne formaty:
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     ePub
     Mobi

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Need to turn your skills at programming into effective data science skills? Principles of Data Science is created to help you join the dots between mathematics, programming, and business analysis. With this book, you’ll feel confident about asking—and answering—complex and sophisticated questions of your data to move from abstract and raw statistics to actionable ideas.
With a unique approach that bridges the gap between mathematics and computer science, this books takes you through the entire data science pipeline. Beginning with cleaning and preparing data, and effective data mining strategies and techniques, you’ll move on to build a comprehensive picture of how every piece of the data science puzzle fits together. Learn the fundamentals of computational mathematics and statistics, as well as some pseudocode being used today by data scientists and analysts. You’ll get to grips with machine learning, discover the statistical models that help you take control and navigate even the densest datasets, and find out how to create powerful visualizations that communicate what your data means.

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O autorze książki

Sinan Ozdemir is a data scientist, start-up founder, and educator living in the San Francisco Bay Area. He studied pure mathematics at the Johns Hopkins University. He then spent several years conducting lectures on data science there, before founding his own start-up, Kylie ai, which uses artificial intelligence to clone brand personalities and automate customer service communications. He is also the author of Principles of Data Science, available through Packt.

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