Foundations of Programming, Statistics, and Machine Learning for Business Analytics. Questo articolo non è disponibile.
Lingua: inglese
Editore: SAGE Publications Ltd, 2023
- Brossura
- Nuovo

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Codice articolo B9781529620917
- Titolo
- Foundations of Programming, Statistics, and Machine Learning for Business Analytics
- Autore
- Ram Gopal
- Editore
- SAGE Publications Ltd
- Anno di pubblicazione
- 2023
- Condizione
- New
- Rilegatura
- Paperback / softback
- Lingua
- inglese
- ISBN 10
- 1529620910
- ISBN 13
- 9781529620917
- Peso dell'articolo
- 220 grammi
Business Analysts and Data Scientists are in huge demand, as global companies seek to digitally transform themselves and leverage their data resources to realize competitive advantage.
This book covers all the fundamentals, from statistics to programming to business applications, to equip you with the solid foundational knowledge needed to progress in business analytics.
Assuming no prior knowledge of programming or statistics, this book takes a simple step-by-step approach which makes potentially intimidating topics easy to understand, by keeping Maths to a minimum and including examples of business analytics in practice.
Key features:
· Introduces programming fundamentals using R and Python
· Covers data structures, data management and manipulation and data visualization
· Includes interactive coding notebooks so that you can build up your programming skills progressively
Suitable as an essential text for undergraduate and postgraduate students studying Business Analytics or as pre-reading for students studying Data Science.
Ram Gopal is Pro-Dean and Professor of Information Systems at the University of Warwick.
Daniel Philps is an Artificial Intelligence Researcher and Head of Rothko Investment Strategies.
Tillman Weyde is Senior Lecturer at City, University of London.
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Informazioni sull’autore
Dan Philps is a veteran quantitative investment manager and a widely published artificial intelligence (AI) researcher.
Tillman Weyde is a Reader in Computer Science at City, University of London. Before joining City in 2005, he worked as a researcher in the Research Department for Music and Media Technology at the University of Osnabrück.
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