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Opiniones y comentarios de aprendices correspondientes a Pattern Discovery in Data Mining por parte de Universidad de Illinois en Urbana-Champaign

4.3
estrellas
302 calificaciones
57 reseña

Acerca del Curso

Learn the general concepts of data mining along with basic methodologies and applications. Then dive into one subfield in data mining: pattern discovery. Learn in-depth concepts, methods, and applications of pattern discovery in data mining. We will also introduce methods for data-driven phrase mining and some interesting applications of pattern discovery. This course provides you the opportunity to learn skills and content to practice and engage in scalable pattern discovery methods on massive transactional data, discuss pattern evaluation measures, and study methods for mining diverse kinds of patterns, sequential patterns, and sub-graph patterns....

Principales reseñas

GL

17 de ene. de 2018

Excellent course. Now I have a big picture about pattern discovery and understand some popular algorithm. Also professor points out the direction for further study.

DD

9 de sep. de 2017

The first several chapters are very impressive. The last three lessons are a little difficult for first-learners. The illustration are clear and easy to understand.

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26 - 50 de 57 revisiones para Pattern Discovery in Data Mining

por SAURABH K

2 de feb. de 2019

nice

por Mauricio B V

12 de nov. de 2016

I like this course. Its provides a good base for pattern discovery, with useful high level techniques, this can be used as a starting point.

Something to improve can be incorporating at least one lesson with best practice coding techniques to solve the practical exercises.

por Jose A E H

2 de may. de 2017

It's an introductory course to key Pattern Discovery techniques with a comprehensive coverage of important subjects. However, it should be complemented by following the referenced material in order to obtain a wider and more complete picture of the field.

por Hidetake T

31 de mar. de 2020

There are only two programming assignments. One more assignment will gives learners much more confidence I guess. But there are no other similar courses in MOOC. So, worth to take it.

por Clark Y

31 de ene. de 2017

I learned a lot from this lecture. And I believe the lecture is excellent except that if he could become a little bit funny, then it would be perfect. Thanks,

Clark

por Cheng-shuo Y

12 de dic. de 2017

It is a good course but more knowledge are expected to be filled, e.g, some algorithm can be detailed or illustrated with simple-case instantiation.

por 邓文豪

21 de sep. de 2020

The course is relatively easy to understand and points out the direction for further study.

por V B

9 de ago. de 2019

Large variety of algorithm presented. Good study material recommendations. Fun assignments.

por Gary C

27 de jun. de 2017

Excellent course that summarizes a very broad and complex topic. Definitely recommend.

por Alexander S

16 de dic. de 2019

Good course. The explanation for the optional programming assignment is very poor.

por Rahul M

5 de mar. de 2017

The course exercises are medium-hard. But the topic coverage is spot on.

por Jaroslaw G

11 de nov. de 2017

OK course, some lectures with too much breadth at the cost of depth

por Tanan K

23 de abr. de 2017

Should be more support in the forum for quiz and assignement

por Lerata M

11 de may. de 2021

Sigh, algorithms are not a walk in the park!

por Piotr B

3 de ago. de 2017

Too much material. Not enough real examples.

por Limber

28 de nov. de 2017

I don't really like the Programming Assignment of this course.

I have took over one month to figure it out, and the feedback system don't even provide me any help. The day that I have registered for this course, the coding is still new to me although I have got the training like 1 year thanks to Andrew Ng. And I could only used MATLAB/Octave or Python to solve the quiz. I have tried to use MATLAB to finished this course, but I failed many times. Finally, I have decided to use Python to solve this PA, and the algorithm is still hard for me to complete, so I used the python tool that with the algorithm in it and fix a little.

I believe that this course is a really good course, and Jiawei Han is a real kind person. BUT even for some other courses, we got a startup(like Andrew Ng's Machine Learning Course and Koller's PGM).

However, besides the PA, the rest of the course is really worth taking. I read the books for times and figured out that it indeed help! Though, it is hard for a new student. You should have to dive deep into the course which you should read more about this subject. Jiawei Han's work is only a startup.

Thank you very much.

por To P H

8 de may. de 2019

Course content too dense with many lectures serve as mere summary of advanced papers with little explanantion of technical terms. Too much mention of advanced topics with not enough coverage and depth for each topic

There are not many examples of the algorithm/of a case that can be solved using an algorithm. Little math is involved

Course should be longer (6 weeks) with longer lectures with more examples and exercises

This makes the content quick to be forgotten.

por Robert R

28 de may. de 2017

Solid introduction with a lot of references.

Lot of topics are not deep enough discussed and a lot of additional reading is necessary in order to get a lot out of the course. Furthermore, the presentation style and the (language) understandability of the lecturer are not very good. Too few exercise questions. Would still recommend it as introduction course and for the high number of good paper references.

por Aleksandra H

26 de may. de 2019

Briefly described a lot of stuff that could have been explained more visually and demonstrated with step-by-step examples more often. This might be expected for a 4-week course, but it would have been nice to extend it instead of trying to fit it into a compressed time frame. The required programming assignment could have been clearer about how the work should be structured and submitted.

por Sergey

12 de feb. de 2019

A good overview of data mining. The course turned out to be quite casual, with many quizzes requiring only knowledge of some definitions which disappeared from my short-lived memory in no time. I suppose it is based on a much more detailed and challenging one taught at the University of Illinois. On the other hand, programming assignments were fun.

por Logan J T

15 de may. de 2018

I would prefer to see this class split into two. I felt topics did not receive enough time to truly learn them. I would also like to see a more advanced course that required programming assignments.

por Alan J R

20 de feb. de 2020

Way too hard to find out whta the teacher was talking abut, had to make too much research on texts. Specially about CP-Miner. For the rest, great!

por Devender B

6 de mar. de 2019

One star less because of errors in the quiz questions which is not acceptable when it is mandatory to pass

por Red R

18 de ene. de 2022

C​ertain lectures unclear

por Raj A S

11 de abr. de 2019

very time consuming