SØG - mellem flere end 8 millioner bøger:
Viser: Marketing Data Science - Modeling Techniques in Predictive Analytics with R and Python
Marketing Data Science Vital Source e-bog
Thomas W. Miller
(2015)
Marketing Data Science Vital Source e-bog
Thomas W. Miller
(2015)
Marketing Data Science Vital Source e-bog
Thomas W. Miller
(2015)
Marketing Data Science
Modeling Techniques in Predictive Analytics with R and Python
Thomas Miller
(2015)
Sprog: Engelsk
om ca. 10 hverdage
Detaljer om varen
- 1. Udgave
- Vital Source 180 day rentals (dynamic pages)
- Udgiver: Pearson International (Maj 2015)
- ISBN: 9780133887341R180
Bookshelf online: 180 dage fra købsdato.
Bookshelf appen: 180 dage fra købsdato.
Udgiveren oplyser at følgende begrænsninger er gældende for dette produkt:
Print: 2 sider kan printes ad gangen
Copy: højest 2 sider i alt kan kopieres (copy/paste)
Detaljer om varen
- 1. Udgave
- Vital Source 90 day rentals (dynamic pages)
- Udgiver: Pearson International (Maj 2015)
- ISBN: 9780133887341R90
Bookshelf online: 90 dage fra købsdato.
Bookshelf appen: 90 dage fra købsdato.
Udgiveren oplyser at følgende begrænsninger er gældende for dette produkt:
Print: 2 sider kan printes ad gangen
Copy: højest 2 sider i alt kan kopieres (copy/paste)
Detaljer om varen
- 1. Udgave
- Vital Source 365 day rentals (dynamic pages)
- Udgiver: Pearson International (Maj 2015)
- ISBN: 9780133887341R365
Bookshelf online: 5 år fra købsdato.
Bookshelf appen: 5 år fra købsdato.
Udgiveren oplyser at følgende begrænsninger er gældende for dette produkt:
Print: 2 sider kan printes ad gangen
Copy: højest 2 sider i alt kan kopieres (copy/paste)
Detaljer om varen
- Hardback: 480 sider
- Udgiver: Pearson Education, Limited (Maj 2015)
- ISBN: 9780133886559
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.