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Hands-on data science for marketing : improve your marketing strategies with machine learning using Python and R /

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자료유형E-Book
개인저자Hwang, Yoon Hyup, author.
서명/저자사항Hands-on data science for marketing :improve your marketing strategies with machine learning using Python and R /Yoon Hyup Hwang.
발행사항Birmingham, UK : Packt Publishing, 2019.
형태사항1 online resource : illustrations
소장본 주기Added to collection customer.56279.3
ISBN178934882X
9781789348828

내용주기Cover; Title Page; Copyright and Credits; About Packt; Contributors; Table of Contents; Preface; Section 1: Introduction and Environment Setup; Chapter 1: Data Science and Marketing; Technical requirements; Trends in marketing; Applications of data science in marketing; Descriptive versus explanatory versus predictive analyses; Types of learning algorithms; Data science workflow; Setting up the Python environment; Installing the Anaconda distribution; A simple logistic regression model in Python; Setting up the R environment; Installing R and RStudio; A simple logistic regression model in R
Chapter 3: Drivers behind Marketing EngagementUsing regression analysis for explanatory analysis; Explanatory analysis and regression analysis; Logistic regression; Regression analysis with Python; Data analysis and visualizations; Engagement rate; Sales channels; Total claim amounts; Regression analysis; Continuous variables; Categorical variables; Combining continuous and categorical variables; Regression analysis with R; Data analysis and visualization; Engagement rate; Sales channels; Total claim amounts; Regression analysis; Continuous variables; Categorical variables
Combining continuous and categorical variablesSummary; Chapter 4: From Engagement to Conversion; Decision trees; Logistic regression versus decision trees; Growing decision trees; Decision trees and interpretations with Python; Data analysis and visualization; Conversion rate; Conversion rates by job; Default rates by conversions; Bank balances by conversions; Conversion rates by number of contacts; Encoding categorical variables; Encoding months; Encoding jobs; Encoding marital; Encoding the housing and loan variables; Building decision trees; Interpreting decision trees
Decision trees and interpretations with RData analysis and visualizations; Conversion rate; Conversion rates by job; Default rates by conversions; Bank balance by conversions; Conversion rates by number of contacts; Encoding categorical variables; Encoding the month; Encoding the job, housing, and marital variables; Building decision trees; Interpreting decision trees; Summary; Section 3: Product Visibility and Marketing; Chapter 5: Product Analytics; The importance of product analytics; Product analytics using Python; Time series trends; Repeat customers; Trending items over time
요약Section 2: Descriptive Versus Explanatory Analysis; Chapter 2: Key Performance Indicators and Visualizations; KPIs to measure performances of different marketing efforts; Sales revenue; Cost per acquisition (CPA); Digital marketing KPIs; Computing and visualizing KPIs using Python; Aggregate conversion rate; Conversion rates by age; Conversions versus non-conversions; Conversions by age and marital status; Computing and visualizing KPIs using R; Aggregate conversion rate; Conversion rates by age; Conversions versus non-conversions; Conversions by age and marital status; Summary
요약This book will be an excellent resource for both Python and R developers and will help them apply data science and machine learning to marketing with real-world data sets. By the end of this book, you will be well equipped with the required knowledge and expertise to draw insights from data and improve your marketing strategies.
일반주제명Marketing -- Data processing.
Machine learning.
Marketing research.
Python (Computer program language)
R (Computer program language)
Machine learning.
Marketing -- Data processing.
Marketing research.
Python (Computer program language)
R (Computer program language)
언어영어
기타형태 저록Print version:Hwang, Yoon Hyup.Hands-On Data Science for Marketing : Improve Your Marketing Strategies with Machine Learning Using Python and R.Birmingham : Packt Publishing Ltd, 짤20199781789346343
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