Vincent

A Friendly Guide to Data Science

Everything You Should Know About the Hottest Field in Tech

Apress

ISBN 9798868811685

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auch verfügbar als eBook (PDF) für 46,99 €

Bibliografische Daten

Fachbuch

Buch. Softcover

2025

52 s/w-Abbildungen, 107 Farbabbildungen.

In englischer Sprache

Umfang: xxxvi, 884 S.

Format (B x L): 15,5 x 23,5 cm

Verlag: Apress

ISBN: 9798868811685

Weiterführende bibliografische Daten

Das Werk ist Teil der Reihe: Friendly Guides to Technology

auch verfügbar als eBook (PDF) für 46,99 €

Produktbeschreibung

What is data and how does it fit into data science? What does the field of data science cover? What is data analysis and what skills are involved? What does data analytics refer to in the context of data analysis and data science? Data science involves far more than pulling data out of a database and running machine learning. This book teaches you what data science can and cannot do. You also will learn the importance of ethics, security, and privacy considerations. And you will understand the many steps in a data science project and how the project life cycle works. Data science is an important field that’s here to stay, especially as artificial intelligence (AI) and data become part of the everyday conversation in modern society for both their positive and negative impacts. This book’s focus on laying strong foundations makes it highly accessible to anyone interested in taking part in the data science revolution, even if they don’t yet have programming or business experience. It’s perfect for undergraduate and graduate students in data science programs as well as for business leaders and potential career-changers in need of an inviting way into the field. What You Will Learn Know what foundational statistics is and how it matters in data analysis and data science Understand the data science project life cycle and how to manage a data science project Examine the ethics of working with data and its use in data analysis and data science Understand the foundations of data security and privacy Collect, store, prepare, visualize, and present data Identify the many types of machine learning and know how to gauge performance Prepare for and find a career in data science

Autorinnen und Autoren

Kundeninformationen

Covers the breadth of the discipline of real-world data science Includes insightful interviews with practitioners Accessible guidebook even if you do not yet have experience in programming or business

Produktsicherheit

Hersteller

Springer Nature Customer Service Center GmbH

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69115 Heidelberg, DE

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