Production ready recommender engines

In this chapter so far, we have learnt about recommender engines in detail and even developed one from scratch (using matrix factorization). Through all this, it is clearly evident how widespread the application of such systems is.

E-commerce websites (or for that fact, any popular technology platform) out there today have tones of content to offer. Not only that, but the number of users is also huge. In such a scenario, where thousands of users are browsing/buying stuff simultaneously across the globe, providing recommendations to them is a task in itself. To complicate things even further, a good user experience (response times, for example) can create a big difference between two competitors. These are live examples of production systems handling millions of customers day in and day out.

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Fun Fact

Amazon.com is one of the biggest names in the e-commerce space with 244 million active customers. Imagine the amount of data being processed to provide recommendations...