Building Recommendation Engines in Python

We expect personalized experiences online. This could be Netflix suggesting a series or an online retailer suggesting possible products. How do these recommendations come about? This course will show you how to create your own recommendation engine. Through hands-on activities, you will learn about both collaborative and content-based filtering. Next, you will learn how to measure similarities like the Jaccard distance and cosine similarity. You'll also learn how to evaluate the quality of recommendations based upon test data using root means square error (RMSE). This course will teach you how to use Python to create these systems in any industry.