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Item specifics

Condition
Brand new: A new, unread, unused book in perfect condition with no missing or damaged pages. See the ...
Book Title
Foundations of Programming, Statistics, and Machine Learning for
ISBN
9781529620900
Subject Area
Business & Economics
Publication Name
Foundations of Programming, Statistics, and Machine Learning for Business Analytics
Publisher
SAGE Publications, The Limited
Item Length
9 in
Subject
General, Economics / General, Management Science, Statistics
Publication Year
2023
Type
Textbook
Format
Hardcover
Language
English
Author
Tillman Weyde, Dan Philps, Ram Gopal
Item Weight
45.7 Oz
Item Width
7 in
Number of Pages
512 Pages

About this product

Product Identifiers

Publisher
SAGE Publications, The Limited
ISBN-10
1529620902
ISBN-13
9781529620900
eBay Product ID (ePID)
2329415815

Product Key Features

Number of Pages
512 Pages
Language
English
Publication Name
Foundations of Programming, Statistics, and Machine Learning for Business Analytics
Subject
General, Economics / General, Management Science, Statistics
Publication Year
2023
Type
Textbook
Author
Tillman Weyde, Dan Philps, Ram Gopal
Subject Area
Business & Economics
Format
Hardcover

Dimensions

Item Weight
45.7 Oz
Item Length
9 in
Item Width
7 in

Additional Product Features

Intended Audience
College Audience
LCCN
2022-947084
Dewey Edition
23
Illustrated
Yes
Dewey Decimal
658.4/72
Table Of Content
Chapter 1: Introduction To Programming And StatisticsChapter 2: Summarizing And Visualizing DataChapter 3: Summarizing And Visualizing DataChapter 4: Programming FundamentalsChapter 5: Programming FundamentalsChapter 6: DistributionsChapter 7: Statistical Testing - Concepts and StrategyChapter 8: Statistical Testing - Concepts and StrategyChapter 9: Nonparametric TestsChapter 10: Reality CheckChapter 11: Fundamentals of EstimationChapter 12: Linear ModelsChapter 13: General Linear ModelsChapter 14: Regression Diagnostics And StructureChapter 15: Timeseries And ForecastingChapter 16: Introduction To Machine LearningChapter 17: Model Selection And Cross ValidationChapter 18: Regression Models In Machine LearningChapter 19: Classification Models And EvaluationChapter 20: Automated Machine Learning
Synopsis
This book provides an introduction to the key concepts in programming, statistics and machine learning needed by business analytics students, assuming no prior knowledge and taking a step-by-step approach to help students build up their confidence., 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., 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 Gopalis Pro-Dean and Professor of Information Systems at the University of Warwick. Daniel Philpsis an Artificial Intelligence Researcher and Head of Rothko Investment Strategies. Tillman Weydeis Senior Lecturer at City, University of London.
LC Classification Number
HD38.7

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