UMN - Nearest Neighbor Collaborative Filtering
- Offered byCoursera
Nearest Neighbor Collaborative Filtering at Coursera Overview
Duration | 15 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Official Website | Explore Free Course  |
Credential | Certificate |
Nearest Neighbor Collaborative Filtering at Coursera Highlights
- Shareable Certificate Earn a Certificate upon completion
- 100% online Start instantly and learn at your own schedule.
- Course 2 of 5 in the Recommender Systems Specialization
- Flexible deadlines Reset deadlines in accordance to your schedule.
- Approx. 15 hours to complete
- English Subtitles: French, Portuguese (European), Russian, English, Spanish
Nearest Neighbor Collaborative Filtering at Coursera Course details
- 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.
Nearest Neighbor Collaborative Filtering at Coursera Curriculum
Preface
Course Introduction
Course Structure Outline
User-User Collaborative Filtering
Configuring User-User Collaborative Filtering
Influence Limiting and Attack Resistance; Interview with Paul Resnick
Trust-Based Recommendation; Interview with Jen Golbeck
Impact of Bad Ratings; Interview with Dan Cosley
User-User Collaborative Filtering Recommenders Part 2
Assignment Introduction
Programming Assignment - Programming User-User Collaborative Filtering
Assignment Instructions: User-User CF
Introducing User-User CF Programming Assignment
User-User CF Answer Sheet
User-User Collaborative Filtering Quiz
Item-Item Collaborative Filtering Recommenders Part 1
Introduction to Item-Item Collaborative Filtering
Item-Item Algorithm
Item-Item on Unary Data
Item-Item Hybrids and Extensions
Strengths and Weaknesses of Item-Item Collaborative Filtering
Interview with Brad Miller
Item-Item Collaborative Filtering Recommenders Part 2
Item-Based CF Assignment Intro Video
Programming Assignment - Programming Item-Item Collaborative Filtering
Item-Based CF Assignment Instructions
Introducing Item-Item CF Programming Assignment
Item Based Assignment Part l
Item Based Assignment Part II
Item Based Assignment Part III
Item Based Assignment Part IV
The Cold Start Problem
Recommending for Groups: Interview with Anthony Jameson
Threat Models
Explanations
Explanations, Part II: Interview with Nava Tintarev
Item-Based and Advanced Collaborative Filtering Topics Quiz
Nearest Neighbor Collaborative Filtering at Coursera Admission Process
Important Dates
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