Real-world case studies

Now, we will move on to some real-world machine learning scenarios. First, we will build a recommender system, and then we will look into some integrated pest management systems in greenhouses.

Building a recommender system

Recommender systems are a type of information filtering, and there are two general approaches: content-based filtering and collaborative filtering. In content-based filtering, the system attempts to model a user's long term interests and select items based on this. On the other hand, collaborative filtering chooses items based on the correlation with items chosen by people with similar preferences. As you would expect, many systems use a hybrid of these two approaches.

Content-based filtering

Content-based filtering uses the content of items, which is represented as a set of descriptor terms, and matches them with a user profile. A user profile is constructed using the same terms extracted from items that the user has previously viewed. A typical online...