In part 1, we learnt about recommendation engines in general, and looked at ways to implement a service using the Google Cloud Platform (GCP). In part 2 of the blog series, we are getting our hands dirty on the item-similarity model and TensorFlow implementation of it.
This is our first technical blog of the series. Here, I deep dive into the data processing step, the recommendation service, and some hints on how to optimise the code to have real-time responses. You should expect to know how to build a simple item-similarity recommender engine by the end of this blog.
So let’s get the party started!