<p><b>Learn data science by doing data science!</b><b> </b></p><p><b><i>Data Science Using Python and R </i></b><b>will get you plugged into the world¿s two most widespread open-source platforms for data science: Python and R.</b></p><p>Data science is hot. <i>Bloomberg </i>called data scientist ¿the hottest job in America.¿ Python and R are the top two open-source data science tools in the world. In <i>Data Science Using Python and R</i>, you will learn step-by-step how to produce hands-on solutions to real-world business problems, using state-of-the-art techniques. </p><p><i>Data Science Using Python and R</i> is written for the general reader with no previous analytics or programming experience. An entire chapter is dedicated to learning the basics of Python and R. Then, each chapter presents step-by-step instructions and walkthroughs for solving data science problems using Python and R.</p><p>Those with analytics experience will appreciate having a one-stop shop for learning how to
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<b>Step-by-step guide to practising data science techniques with Jupyter notebooks</b><br/><br/><b>Description</b><br/>Modern businesses are awash with data, making data driven decision-making tasks increasingly...
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<b>Summary</b><BR><BR>Dask is a native parallel analytics tool designed to integrate seamlessly with the libraries you''re already using, including Pandas, NumPy, and Scikit-Learn. With Dask you can crunch and work with...
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Many of the most famous results in mathematics are impossibility theorems stating that something cannot be done. Good examples include the quadrature of the circle by ruler and compass, the solution of the quintic equation by radicals, Fermat''s...
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