Название: Designing Great Data Products
Автор: Jeremy Howard, Mike Loukides, Margit Zwemer
Издательство: O’Reilly Media
Год издания: 2012
Размер: 5.54 Мб
In the past few years, we’ve seen many data products based on predictive modeling. These products range from weather forecasting to recommendation engines like Amazon’s. Prediction technology can be interesting and mathematically elegant, but we need to take the next step: going from recommendations to products that can produce optimal strategies for meeting concrete business objectives.
We already know how to build these products: they’ve been in use for the past decade or so, but they’re not as common as they should be. This report shows how to take the next step: to go from simple predictions and recommendations to a new generation of data products with the potential to revolutionize entire industries.
Table of Contents
Objective-based data products
The Model Assembly Line: A case study of Optimal Decisions Group
Drivetrain Approach to recommender systems
Optimizing lifetime customer value
Best practices from physical data products
The future for data products
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