Assuming you’re an internet user (which seems likely), you use or encounter recommendation systems all the time. Whenever you see an ad or product that seems eerily in tune with whatever you were just thinking about, it’s because of a recommendation system. In this course, you’ll learn how to build a variety of these systems using Python, and be well on your way to a high-paying career.
- Access 20 lectures & 4.5 hours of content 24/7
- Build Recommendation Engines that use content based filtering to find products that are most relevant to users
- Discover Collaborative Filtering, the most popular approach to recommendations
- Identify similar users using neighborhood models like Euclidean Distance, Pearson Correlation & Cosine
- Use Matrix Factorization to identify latent factor methods
- Learn recommendation systems by building a movie-recommending app in Python
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