Free Marketing Data Science: Modeling Techniques in Predictive Analytics with R and Python (FT Press Analytics)

Description Marketing Data Science: Modeling Techniques in Predictive Analytics with R and Python (FT Press Analytics)

Now, a leader 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 Miller's pioneering program, Marketing Data Science thoroughly addresses 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 Miller's 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. Marketing Data Science will be an invaluable resource for all students, faculty, and professional marketers who want to use business analytics to improve marketing performance.

Marketing Data Science: Modeling Techniques in Predictive Analytics with R and Python (FT Press Analytics) PDF ePub

Modeling Techniques in Predictive Analytics ~ growth of R and the ease of growing it further ensures that the R envi-ronment for modeling techniques in predictive analytics will be around for many years to come. Genie out of the lamp, wizard from behind the curtain—rocket science is not what it usedto be. Secrets are being revealed. This book is part of the process.

Modeling Techniques in Predictive Analytics with Python and R ~ iv Modeling Techniques in Predictive Analytics with Python and R 10 Spatial Data Analysis 211 11 Brand and Price 239 12 The Big Little Data Game 273 A Data Science Methods 277 A.1 Databases and Data Preparation 279 A.2 Classical and Bayesian Statistics 281 A.3 Regression and Classification 284 A.4 Machine Learning 289 A.5 Web and Social Network Analysis 291 A.6 Recommender Systems 293

Marketing Data Science: Modeling Techniques in Predictive ~ Description. 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 .

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Marketing Data Science: Modeling Techniques in Predictive ~ Now, a leader 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.

Marketing Data Science: Modeling Techniques in Predictive ~ He has designed courses for the program, including Marketing Analytics, Advanced Modeling Techniques, Data Visualization, Web and Network Data Science, and the capstone course. He has taught extensively in the program and works with more than forty other faculty members in delivering training in predictive analytics and data science.

Modeling Techniques in Predictive Analytics with Python ~ Modeling Techniques in Predictive Analytics with Python and R: A Guide to Data Science (FT Press Analytics) [Miller, Thomas] on . *FREE* shipping on qualifying offers. Modeling Techniques in Predictive Analytics with Python and R: A Guide to Data Science (FT Press Analytics)

Modeling Techniques in Predictive Analytics with Python ~ Description. Today, successful firms win by understanding their data more deeply than competitors do. They compete based on analytics.In Modeling Techniques in Predictive Analytics, the Python edition, the leader of Northwestern University’s prestigious analytics program brings together all the up-to-date concepts, techniques, and Python code you need to excel in analytics.

Modeling Techniques in Predictive Analytics with Python ~ Compete on analytics: win by understanding your data more deeply than your competitors do! In Modeling Techniques in Predictive Analytics, the Python edition, the leader of Northwestern University's prestigious analytics program brings together all the up-to-date concepts, techniques, and Python code you need to excel in analytics. Thomas W. Miller's balanced approach combines business context .

Marketing Data Science : Thomas Miller : 9780133886559 ~ Thomas W. Miller is faculty director of the Predictive Analytics program at Northwestern University. He has designed courses for the program, including Marketing Analytics, Advanced Modeling Techniques, Data Visualization, Web and Network Data Science, and the capstone course.

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More Free Data Mining, Data Science Books and Resources ~ More free resources and online books by leading authors about data mining, data science, machine learning, predictive analytics and statistics. The list below based on the list compiled by Pedro Martins, but we added the book authors and year, sorted alphabetically by title, fixed spelling, and removed the links that did not work.

Descriptive, Predictive and Prescriptive Analytics Explained ~ Predictive Analytics: Understanding the future. Predictive analytics has its roots in the ability to “predict” what might happen. These analytics are about understanding the future. Predictive analytics provides companies with actionable insights based on data. Predictive analytics provides estimates about the likelihood of a future outcome.

Top 30 Best Business Analytics Books You Should Read ~ “Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner, Third Edition is an ideal textbook for upper-undergraduate and graduate-level courses as well as professional programs on data mining, predictive modeling, and Big Data analytics.

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Meaningful Predictive Modeling / Coursera ~ Finally, you’ll use design thinking methodology and data science techniques to extract insights from a wide range of data sources. This is your chance to master one of the technology industry’s most in-demand skills. Python Data Products for Predictive Analytics is taught by Professor Ilkay Altintas, Ph.D. and Julian McAuley. Dr.

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