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William Vorhies's Blog – January 2017 Archive (5)

Deep Learning and Recommenders

Summary:  In this last article in our series on recommenders we look to the future to see how the rapidly emerging capabilities of Deep Learning can be used to enhance recommender performance. 

 

In our first article, “Understanding…

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Added by William Vorhies on January 31, 2017 at 9:30am — No Comments

Recommenders: Packaged Solutions or Home Grown

Summary:  There are many sources of packaged recommenders including the more comprehensive Digital Personalization platforms.  It’s also possible to code your own.  Here are a few things to consider.

 

In our first article, “…

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Added by William Vorhies on January 24, 2017 at 2:00pm — No Comments

5 Types of Recommenders

Summary:  There are five basic styles of recommenders differentiated mostly by their core algorithms.  You need to understand what’s going on inside the box in order to know if you’re truly optimizing this critical tool.

 

In our first article, “…

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Added by William Vorhies on January 17, 2017 at 9:00am — 2 Comments

Understanding and Selecting Recommenders

Summary:  In this multi-part series we walk through the full landscape of Recommenders.  In this article we cover business considerations as well as issues for Recommenders as a group.  In the next articles we’ll discuss the details of the five major types of recommenders, improving their performance, and finally the coming impact of deep learning on Recommenders.

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Added by William Vorhies on January 10, 2017 at 9:00am — 4 Comments

AI Saves the Elephants, Sharks, Frogs, Sea Birds and Everything Else

Summary:  As deep learning expands those capabilities are finding their way into the not-for-profit community in the service of conserving the earth’s wildlife and forests.

 

The for-profit world may be driving AI but it’s a solution to many problems in the not-for-profit world as well.  We were particularly impressed by the use of…

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Added by William Vorhies on January 3, 2017 at 10:11am — No Comments

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