PySpark Tutorial : Recommendation Engine Types and Data Types

Want to learn more? Take the full course at https://learn.datacamp.com/courses/recommendation-engines-in-pyspark at your own pace. More than a video, you'll learn hands-on coding & quickly apply skills to your daily work. --- In the world of recommendation engines, there are two basic types: Collaborative-filtering engines and content-based filtering engines. Both aim to offer meaningful recommendations, but they do so in slightly different ways. Content-based filtering, as the name suggests, tries to understand the content, or {{1}} features of the items, and makes recommendations based on your preferences for those specific features. For example, a movie streaming service might go to great lengths to add descriptive tags to their movies such as the genre, whether it's animated or not, the language spoken in the movie, the decade it was filmed, and which actors were in it, etc. So when a user like you gives 5 stars to a really dramatic, Portuguese movie with specific actors from a specific decade, they can infer that you like movies like this and will also like other dramatic movies in Portuguese with those same actors, and recommend those movies to you. Collaborative filtering is a little bit different. As explained in the previous video, collaborative filtering is based on user similarity. However, unlike content-based filtering, manually-created tags are not necessary. The features and groupings are created mathematically from patterns in the ratings provided by users. When you provide ratings for a product or item, whether it be a thumbs up or thumbs down, or even if you just watch a video without even giving it a rating, you are providing meaningful insight about your preferences. From this behavior, the ALS algorithm can mathematically group you with similar users, predict your behavior, and help you have a more effective customer experience. While ALS can have content-based applications, this course will focus on it's application to collaborativ