Use case: Recommend items

- [Instructor] In this lecture,…we are going to see an implementation…of the use case for building recommendations.…So when a customer comes to your website…and has bought a product,…you want to recommend him products…that similar people bought.…So in this exercise, we're going to use data about…which customers bought which product…and, based on that, build an item to item affinity score,…and then use it for recommendation.…The exercise files are available under the folder 03_05.…

The data file is the ratings.csv,…and the notebook is the Recommendations.…This is the data file.…So data file is very simple, which user bought which item.…So we have user IDs and item IDs.…So users 1,001…seem to have bought 5,001, 5,002, and 5,005,…and so on, pretty simple, straightforward data file.…Moving on to the notebook,…the notebook is the Recommendations notebook…that we just talked about.…

What we're going to do here is, first,…we're going to load the ratings.csv file and take a look at it.…Now we have to build an affinity score between items…