The knowledge-based recommender

In this section, we are going to go ahead and build a knowledge-based recommender on top of our IMDB Top 250 clone. This will be a simple function that will perform the following tasks:

1. Ask the user for the genres of movies he/she is looking for
2. Ask the user for the duration
3. Ask the user for the timeline of the movies recommended
4. Using the information collected, recommend movies to the user that have a high weighted rating (according to the IMDB formula) and that satisfy the preceding conditions

The data that we have has information on the duration, genres, and timelines, but it isn't currently in a form that is directly usable. In other words, our data needs to be wrangled before it can be put to use to build this recommender.

In our Chapter3 folder, let's create a new Jupyter Notebook named Knowledge Recommender. This notebook will...