Data Science: The Hard Parts - Vaughan, Daniel
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This practical guide provides a collection of techniques and best practices that are generally overlooked in most data engineering and data science pedagogy. Taken as a whole, the lessons in this book make the difference between an average data scientist candidate and a qualified data scientist working in the field.

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Produktbeschreibung
This practical guide provides a collection of techniques and best practices that are generally overlooked in most data engineering and data science pedagogy. Taken as a whole, the lessons in this book make the difference between an average data scientist candidate and a qualified data scientist working in the field.
Autorenporträt
Daniel Vaughan is currently the Head of Data at Clip, the leading paytech company in Mexico. He is the author of Analytical Skills for AI and Data Science (O'Reilly, 2020). With more than 15 years of experience developing machine learning and more than eight years leading data science teams, he is passionate about finding ways to create value through data and data science and in developing young talent. He holds a PhD in economics from NYU (2011). In his free time he enjoys running, walking his dogs around Mexico City, reading, and playing music.