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Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they're also a good way to dive into the;
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From the author of the bestsellers, Data Scientist and Julia for Data Science, this book covers four foundational areas of data science;
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This is a first-principles-based, practical introduction to the fundamentals of data science aimed at the mathematically-comfortable reader;
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Jump-start your career as a data scientist-learn to develop datasets for exploration, analysis, and machine learning SQL for Data;
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clearly pays dividends to be in the know. This friendly guide charts a path through the fundamentals of data science and then delves into the;
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Data science and machine learning-two of the world's hottest fields-are attracting talent from a wide variety of technical, business, and;
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is aimed at data analysts and aspiring data scientists who have a basic knowledge of Julia or are completely new to it. The book also appeals to;
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project examples, this is the book for you. Whether you are brand new to data science or you are a seasoned expert, you will benefit from learning;
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