In this course, you will learn the fundamental techniques for making personalized recommendations through nearest-neighbor techniques. First you will learn user-user collaborative filtering, an algorithm that identifies other people with similar tastes to a target user and combines their ratings to make recommendations for that user. You will explore and implement variations of the user-user algorithm, and will explore the benefits and drawbacks of the general approach. Then you will learn the widely-practiced item-item collaborative filtering algorithm, which identifies global product associations from user ratings, but uses these product associations to provide personalized recommendations based on a user's own product ratings.
Get started with custom lists to organize and share courses.
Sign upClass Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.
Nearest Neighbor Collaborative Filtering
University of Minnesota via Coursera
Found in
Artificial Intelligence
Never miss a course! Add as "Interested" to get notified of this course's next session
- Provider Coursera
- Cost Free Online Course (Audit)
- Session In progress
- Language English
- Certificate Paid Certificate Available
- Start Date
- Duration 4 weeks long
- Learn more about MOOCs
Taken this course? Share your experience with other students. Write review
Become a Data Scientist datacamp.com
Learn Python & R at your own pace. Start now for free!
AD
Class Central Custom Lists
Build and share your own catalog of courses with Class Central's custom lists.
Overview
Class Central Tips
Syllabus
Preface
-Note that this course is structured into two-week chunks. The first chunk focuses on User-User Collaborative Filtering; the second chunk on Item-Item Collaborative Filtering. Each chunk has most of the lectures in the first week, and assignments/quizzes and advanced topics in the second week. We encourage learners to treat each two-week chunk as one unit, starting the assignments as soon as they feel they have learned enough to get going.
User-User Collaborative Filtering Recommenders Part 1
User-User Collaborative Filtering Recommenders Part 2
Item-Item Collaborative Filtering Recommenders Part 1
Item-Item Collaborative Filtering Recommenders Part 2
Advanced Collaborative Filtering Topics
-Note that this course is structured into two-week chunks. The first chunk focuses on User-User Collaborative Filtering; the second chunk on Item-Item Collaborative Filtering. Each chunk has most of the lectures in the first week, and assignments/quizzes and advanced topics in the second week. We encourage learners to treat each two-week chunk as one unit, starting the assignments as soon as they feel they have learned enough to get going.
User-User Collaborative Filtering Recommenders Part 1
User-User Collaborative Filtering Recommenders Part 2
Item-Item Collaborative Filtering Recommenders Part 1
Item-Item Collaborative Filtering Recommenders Part 2
Advanced Collaborative Filtering Topics
Taught by
Joseph A Konstan and Michael D. Ekstrand
Tags
Help Center
Reviews
for Coursera's Nearest Neighbor Collaborative Filtering
Based on
2 reviews
- 5 star 0%
- 4 star 0%
- 3 star 50%
- 2 star 0%
- 1 star 50%
Did you take this course? Share your experience with other students.
Write a review- 1
Stephane M
3 years ago
completed this course.
1
person found
this review helpful
this review helpful
Was this review helpful to you?
Yes
Alex I
3 years ago
completed this course.
0
person found
this review helpful
this review helpful
Was this review helpful to you?
Yes
- 1
Class Central
Get personalized course recommendations, track subjects and courses with reminders, and more.
Never Stop Learning!
Get personalized course recommendations, track subjects and courses with reminders, and more.
