A recommendation system for blogs: Setting up the prerequisites [1/3] via @m__technologist

This is the first in a series of three blog posts where Thom Hopmans will elaborate on how we can build a recommendation engine for the readers on The Marketing Technologist (TMT). TMT currently has over fifty blog posts covering varying topics from Data Science to coding in ReactJS. Browsing through all the blog posts is time consuming, especially as the number of posts is still increasing. Also chances are readers are only interested in a select few blog posts that lie in their area of interest. If a recommendation engine is able to select those articles an user is interested in then this can definitely be classified as creating value from data and preventing information overload.

Nice start to the set of three blogs which takes you through some of the thought steps to follow as well comments on how to do it in Python. Good to look at even if you are not into Python.