Overview
Context
We’ve come to expect personalized experiences online—whether it’s Netflix recommending a show or an online retailer suggesting items you might also like to purchase. But how are these suggestions generated?
In this Building Recommendation Engines in Python course at Data Camp, you’ll learn everything you need to know to create your own recommendation engine.
Through hands-on exercises, you’ll get to grips with the two most common systems, collaborative filtering and content-based filtering.
Next, you’ll learn how to measure similarities like the Jaccard distance and cosine similarity, and how to evaluate the quality of recommendations on test data using the root mean square error (RMSE).
Programme Structure
Chapters
- Content-Based Recommendations
- Collaborative Filtering
- Matrix Factorization and Validating Your Predictions
Key information
Duration
- Part-time
- 1 days
Start dates & application deadlines
Language
Delivered
Disciplines
Software Engineering View 485 other Short Courses in Software Engineering in United StatesAcademic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
PREREQUISITES
- Supervised Learning with scikit-learn
- Data Manipulation with pandas
Tuition Fee
-
International
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 1 days. -
National
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 1 days.
Basic Access: Free; Premium (for individuals): $12.42 per month billed annually; Teams: $25 per month billed annually; Enterprise: Contact sales for pricing