Description: Marketing Data Science : Modeling Techniques in Predictive Analytics With R and Python, Hardcover by Miller, Thomas W., ISBN 0133886557, ISBN-13 9780133886559, Brand New, Free shipping in the US In Marketing Data Science, a top faculty member of Northwestern University's prestigious analytics program presents a fully-integrated treatment of both the business and academic elements of marketing applications in predictive analytics. Writing for both managers and students, Thomas W. Miller explains essential concepts, principles, and theory in the context of real-world applications. Building on his predictive analytics program at Northwestern, Miller covers segmentation, target marketing, brand and product positioning, new product development, choice modeling, recommender systems, pricing research, retail site selection, demand estimation, sales forecasting, customer retention, and lifetime value analysis. Starting where his widely-praised Modeling Techniques in Predictive Analytics left off, he integrates crucial information and insights that were previously segregated in texts on web analytics, network science, information technology, and programming. Coverage includes: The role of analytics in delivering effective messages on the web Understanding the web by understanding its hidden structures Being recognized on the web – and watching your own competitors Visualizing networks and understanding communities within them Measuring sentiment and making recommendations Leveraging key data science methods: databases/data preparation, classical/Bayesian statistics, regression/classification, machine learning, and text analytics Six complete case studies address exceptionally relevant issues such as: separating legitimate email from spam; identifying legally-relevant information for lawsuit discovery; gleaning insights from anonymous web surfing data, and more. This text's extensive set of web and network problems draw on rich public-domain data sources; many are accompanied by solutions in Python and/or R.
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Book Title: Marketing Data Science : Modeling Techniques in Predictive Analyt
Number of Pages: 480 Pages
Publication Name: Marketing Data Science : Modeling Techniques in Predictive Analytics with Rand Python
Language: English
Publisher: Pearson Education
Publication Year: 2015
Subject: Marketing / General, Operations Research, Databases / Data Mining, Statistics
Item Height: 1.4 in
Type: Textbook
Item Weight: 34.4 Oz
Item Length: 9.3 in
Author: Thomas Miller
Subject Area: Computers, Technology & Engineering, Business & Economics
Item Width: 7.1 in
Series: Ft Press Analytics Ser.
Format: Hardcover
