By Michael S. Malak and Robin East
Semi-supervised learning combines the best of both worlds of supervised learning and unsupervised learning. In this article, excerpted from Spark GraphX in Action, we talk about semi-supervised learning.
By Kim Falk
In this article, excerpted from my book Practical Recommender Systems, I explain the concept of “evidence” using Netflix.
By Doug Turnbull, author of Relevant Search
How do you solve an applied relevance problem? What process can you define that incorporates both some of the narrower, domain-specific data points that influence your relevance along with Information Retrieval techniques? In this article, we discuss the applied relevance problem.
By Simon Holmes, author of Getting MEAN with Mongo, Express, Angular, and Node
Coding in SPAs (Single Page Applications) is most likely a vast improvement on what you’ve been doing before, but it may not always be the best solution. Here’s a brief look at some things to bear in mind about SPAs when designing a solution, and how to decide whether a full SPA is right for your project.