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Market Basket Analysis in R
4.8(93)5k studentsINTERMEDIATEEnglish
Korshub's take
The Korshub Take
This intermediate R course teaches how to uncover hidden associations between products in shopping baskets using Market Basket Analysis. You will learn to quantify item co-occurrence and build movie recommendation systems based on user viewing patterns.
Who It's For
Retail analysts, marketers, and R programmers looking to discover product relationships and craft personalized recommendation engines.
Key Takeaways
- Association Rule Mining: Extract and quantify relationships between frequently co-purchased items using association rules.
- Rule Visualization: Filter, evaluate, and visually analyze insightful basket rules to extract retail intelligence.
- Recommendation Engine: Apply association mining to a movie dataset to predict co-watched titles and recommend personalized content.
About this course
Last time you were at the supermarket, what was in your shopping basket? Was there a connection between the products you purchased, like spaghetti and tomatoes or ham and pineapple? Whether online or offline, retailers use information from millions of customer’s baskets to analyze associations between items and extract insights using association rules.
To help you quantify the degree of association between items you’ll use market basket analysis to uncover unseen connections and visualize relevant and insightful rules. You’ll then get to practice what you’ve learned on a movie dataset, as you predict which movies are watched together to create personalized movie recommendations for users.
Price
Free
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