From the course: Building a Recommendation System with Python Machine Learning & AI
Join today to access over 22,600 courses taught by industry experts or purchase this course individually.
Content-based recommender systems - Python Tutorial
From the course: Building a Recommendation System with Python Machine Learning & AI
Content-based recommender systems
- [Instructor] The last type of recommender I want to cover is content-based recommendation systems. These type of recommenders are not collaborative filtering systems because user preferences and attitudes do not weigh into the evaluation. Instead, content-based recommenders recommend an item based on its features and how similar those are to features of other items in a dataset. In the demo, we're going to use the nearest neighbor algorithm to build a content-based recommender. The nearest neighbor algorithm is an unsupervised classifier. It's also known as a memory-based system, because it memorizes instances and then recommends an item, or a single instance, based on how quantitatively similar it is to a new incoming instance. To conceptualize how to use nearest neighbor algorithm in this capacity, imagine you're a car dealer. You get a customer that comes in and tells you that he wants a car that gets 25 miles per gallon and has a 4.7 liter, 425 horsepower engine. You have a…
Practice while you learn with exercise files
Download the files the instructor uses to teach the course. Follow along and learn by watching, listening and practicing.
Download courses and learn on the go
Watch courses on your mobile device without an internet connection. Download courses using your iOS or Android LinkedIn Learning app.