Joseph A Konstan
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. After completing this course, you will be able to compute a variety of recommendations from datasets using basic spreadsheet tools, and if you complete the honors track you will also have programmed these recommendations using the open source LensKit recommender toolkit. In addition to detailed lectures and interactive exercises, this course features interviews with several leaders in research and practice on advanced topics and current directions in recommender systems.
Instructor Details
Courses : 2
Specification: Introduction to Recommender Systems: Non-Personalized and Content-Based
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48 reviews for Introduction to Recommender Systems: Non-Personalized and Content-Based
Add a review
| Price | Free |
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| Provider | |
| Duration | 16 hours |
| Year | 2016 |
| Level | Intermediate |
| Language | English |
| Certificate | Yes |
| Quizzes | No |
FREE
Dan T –
great overview of the breadth of material to get started
Julia E –
Thank you very much!
Shuang L –
great professors and inspiring lectures!
Dame N –
Thank you for your course, very Helpfull for those who are keep in touch with recommender System engine. This is a very cool Introduction course.
Daniel P –
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).
Rashid K –
well one thing I am struggling with programming in JAVA. Would not it be handy to have option to do assignment using languages like python/R? which are basically language of choice for data scientists and also easy to have grasp on for newbies. one more thing some time I just get stuck and felt like now way out. I did not get any answer/help form posts on the forum .
Mehmet E –
videos are too long… I had to watch them with x2 speed…
Keshaw S –
Some of the assignments are not particularly well created, in the sense that they seem to emphasize on recalling rather than learning, Also, most of the interview failed to hold my attention in general. Overall, however, this is a very good course and gives a comprehensive overview of the prevalent techniques in the relevant fields.
Yury Z –
Informative and helpfull for me as recommender systems practitioner. Even for things I’ve knew already the authors offer clean and holistic base. Surprisingly the honour track programming assignments was pretty challenging.
Garvit G –
awesome course.
Biswa s –
Good overview on the recommend er system.
Wesley H –
Great introduction to Recommender systems. Really got me thinking about how I could apply them.
Rahul R –
I think some of the interviews didn’t really give me great insights. I know this is only an introduction, but I was expecting more fields than movies. I am overly critical though, all in all a very good way to understand recommendation systems.
shailesh k p –
I am very new to recommendation system and yet able to comprehend the lessons. The best thing is explaining the system with example. Walking through Amazon.com and explaining content based and collaborative filtering is easy to grasp.
Tash B –
Fantastic course. Lecturers have extensive experience in this field. Lectures include interviews with people who have successfully implemented recommender systems in their products or who are researching the permutations, challenges and extensions to recommender system development. Not only does the course provide the chance to build your own recommender systems (optional) but also highlights the complexities and opportunities for refining and improving recommendations. I highly recommend this course to anyone building recommendation systems.
Nicolas A –
Too basic and too repetitive (the videos could be half as long)
tao L –
I think I am on the right track to changing my career from java engineer from data scientist, this course is one of the best start point
sidra n –
I would like to have more detail and help for honors track especially for people like me who do not have much programming experience and want to learn how to implement recommender system. I am unable to solve the assignment and i still need some help. Would be great if the solutions of the honors track should be available to those who want to learn and not just for the sake of getting certificate
Ankur S –
Very informative, very well organized. Especially like the questions like “Which domain would this technique most likely to apply”. Some areas of improvement to consider The overall pace of the content delivery in various lectures could be increased. Tends to get very slow at times More hands on exercises would be useful Programming exercise in Python or Python based frameworks would bee useful
sagar s –
Awesome. Worth it!
LI Z –
Awesome lecture and demonstration. Here are some suggestions, first I think this course may spend too much time on non trivial parts and some parts can be neglected; second, the programming assignment lacks a lot of supplementary tutorial for people who are not familiar with Java and LensKit package.
Md. S R –
The lecturer were very lengthy, at least for me. I find it difficult to concentrate.
Mai H S –
good exercises & lectures
ignacio v –
done it by audit, thnks!!! great stuff guys… but should do some practice in python!
Mustafa S –
Great course
Benjamin S S –
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.
Jon H –
The content of this course is solid. It’s a good introduction to content based and non personailzed recommender systems. However, the presentation is poor. The course is largely based around videos which appear to be single takes. Snappier, well edited videos would have been better and, as a result, I often found myself skimming the transcripts rather than watching the videos.
Joeri K –
It would be nice to have a hierarchical overview of the recommender systems. It’s easy to get lost which is a subcategory of which. Thanks for the course!
shayue –
Really Good! I think it will be helpful to me and take a job for me!
vibhor n –
A good introduction to the basic concepts of recommender systems. Loved the idea of having excel work assignments. For someone just wanting a quick learning of the concepts doesn’t have to go through all the Java stuff
Hagay L –
Overall a good course that teaches the basics for content based recommenders. Would be great if the assignments were a bit more challenging, e.g.: work with large datasets (and not the tiny datasets used in the assignments) Would also be good if we were provided papers of recent/notable research on the topic to read further.
Akash S C –
Good course for basic intro to recommender system. However, some basic problems videos are too long and Java for programming assignment was a huge disappointment. i tried picking the lenskit assignment with java but decided to get rid of it and replicated the assignment in python instead. it was taking too much time to learn Java back which will never be used in regular work for data science. python or R should have been used for prog assignment. time to update the course.
Xinzhi Z –
Great course. I really appreciated the efforts spent by the course team.
Atieno M S –
The course was a good one with content that’s understandable. I can’t wait to proceed to the next one
Su L –
great course, learnt a lot, thanks!
Alex B –
This course mostly works. Contains a lot of wasted video time where no information is communicated. Uses simplistic tools that don’t scale to data applications or otherwise dated tools not really used by data scientists or machine learning engineers making exercises either simplistic or a waste of time. Better than other courses in the series in that the assignments are legible.
Lucas P B –
Was expecting programming activities in Python or R, not in Java /
Julia K –
This course is a wonderful logical informative introduction to several basic types of recommender systems. It is a great part to start! The instructors a clear and well organized. Some assignments were a little bit awkward but overall they
Alejo P –
The course is really well oriented, topics are broadly covered with good explanations and examples. One major drawback of this course is that the honors track is not implemented in Python, though I believe that possibly in future versions this will be adapted. In my case, the two options left are either I learn Java programming or I do not take the honors track.
Muhammad Z H –
Learnt alot
P S –
Nice course
jonghee –
good lecture
Nesreen S –
I found this course very informative. with real life examples of the recommender’s use case and who it can be implemented. I loved that it has an excel assignment to get an intuition about the concepts allowing business like and non techincal audiences to understand and practice the concepts. I found the honor track and assignment though challenging but very important and helpful though the documentation of lenskit was not very clear. it was enjoyable and very useful.
Neha G –
would give negative rating if it was possible, course appears non cohesive and dispersed without any clear terminology being used in the videos. Assignments are not clear either.
Gurupratap S M –
Really a very nice course with great attention to detail. The guest interviews were also superb and gave me exposure to different areas of research in recommender systems in general. Both Michael and Joe are experts and provide deep insights with plenty of examples and study cases. Honors exercises are another added bonus to practice and get hands on experience. I had already deployed a recommender system in production am glad to continue learning and learn different techniques. Thank you once again
Muffaddal Q –
a good course with detail explanation on many aspect of non personalized and content based recommendations. Interviews with experts with excellent. Helped to learn how professionals are solving different problems related to recommendations in their respective fields.
Dhananjay G –
I found this course very useful for me to get in to basics and back ground of recommendations. Each topic is presented and discussed quite in detail . I also found the interviews with various expert in Recommendations very insightful. Thanks you Joe and Micheal.
Michael B –
I feel like the course could’ve been condensed to 1 or 2 weeks max