This course, which is designed to serve as the first course in the Recommender Systems specialization, introduces the concept of recommender systems, reviews several examples in detail, and leads you through non-personalized recommendation using summary statistics and product associations, basic stereotype-based or demographic recommendations, and content-based filtering recommendations.
- 5 stars
- 4 stars
- 3 stars
- 2 stars
- 1 star
来自INTRODUCTION TO RECOMMENDER SYSTEMS: NON-PERSONALIZED AND CONTENT-BASED的热门评论
One of the best courses I have taken on Coursera. Choosing Java for the lab exercises makes them inaccessible for many data scientists. Consider providing a Python version.
Nice introduction to recommender systems for those who have never heard about it before. No complex mathematical formula (which can also be seen by some as a downside).
it's a fantastic course that gives you a good idea of what the objectives of recommender systems are and some intuition on the way how it can be accomplished.
As a software engineer with computer science background I found that course enhancing my knowledge. I'm going to continue the specialization.
Overall, the class is perfect. But if you could supply a sample of honour class when we have finished honour codes, it would be perfect.
More information on Programming Assignment would have been helpful . Overall a good course to begin the specialization
Great course. I have already been able to apply what I have learned to me job. Looking forward to the next one.
The course was a good one with content that's understandable. I can't wait to proceed to the next one
Great introduction to Recommender systems. Really got me thinking about how I could apply them.
Great, thorough introduction with tracks for both Java programmers and non-programmers.
Well-designed assignments and instructive programming exercises in the honors track.
An excellent in-depth introduction into the concepts around recommendation systems!
关于 推荐系统 专项课程
How does this course relate to the prior versions of "Introduction to Recommender Systems"?
This specialization is a substantial extension and update of our original introductory course. It involves about 60% new and extended lectures and mostly new assignments and assessments. This course specifically has added material on stereotyped and demographic recommenders and on advanced techniques in content-based recommendation.