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

Hwang  Yoon Hyup

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dc.contributor.author	Hwang Yoon Hyup
dc.date.accessioned	2024-01-26T21:32:36Z
dc.date.available	2024-01-26T21:32:36Z
dc.date.issued	2019
dc.identifier.citation	Hwang. Hands-on data science for marketing: improve your marketing strategies with machine learning using Python and R - 1 online resource : - URL: https://libweb.kpfu.ru/ebsco/pdf/2094760.pdf
dc.identifier.isbn	178934882X
dc.identifier.isbn	9781789348828
dc.identifier.uri	https://dspace.kpfu.ru/xmlui/handle/net/178265
dc.description.abstract	Section 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
dc.description.tableofcontents	Cover; 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
dc.description.tableofcontents	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
dc.description.tableofcontents	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
dc.description.tableofcontents	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
dc.language	English
dc.language.iso	en
dc.subject.other	Marketing -- Data processing.
dc.subject.other	Machine learning.
dc.subject.other	Marketing research.
dc.subject.other	Python (Computer program language)
dc.subject.other	R (Computer program language)
dc.subject.other	Machine learning.
dc.subject.other	Marketing -- Data processing.
dc.subject.other	Marketing research.
dc.subject.other	Python (Computer program language)
dc.subject.other	R (Computer program language)
dc.subject.other	Electronic books.
dc.title	Hands-on data science for marketing: improve your marketing strategies with machine learning using Python and R/ Yoon Hyup Hwang.
dc.type	Book
dc.description.pages	1 online resource :
dc.collection	Электронно-библиотечные системы
dc.source.id	EN05CEBSCO05C975