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Applied Text Mining in Python(으)로 돌아가기

미시건 대학교의 Applied Text Mining in Python 학습자 리뷰 및 피드백

4.2
2,114개의 평가
397개의 리뷰

강좌 소개

This course will introduce the learner to text mining and text manipulation basics. The course begins with an understanding of how text is handled by python, the structure of text both to the machine and to humans, and an overview of the nltk framework for manipulating text. The second week focuses on common manipulation needs, including regular expressions (searching for text), cleaning text, and preparing text for use by machine learning processes. The third week will apply basic natural language processing methods to text, and demonstrate how text classification is accomplished. The final week will explore more advanced methods for detecting the topics in documents and grouping them by similarity (topic modelling). This course should be taken after: Introduction to Data Science in Python, Applied Plotting, Charting & Data Representation in Python, and Applied Machine Learning in Python....

최상위 리뷰

GK

May 04, 2019

Lectures are very good with a perfect explanation. More than lectures I liked the assignment questions. They are worth doing. You will get to know the basic foundation of text mining. :-)

CB

Sep 20, 2017

Excellent course! Video lectures are high quality, with realistic problems and applications. Exercises are reasonably challenging, and all quite fun to do! Strongly recommend this course

필터링 기준:

Applied Text Mining in Python의 390개 리뷰 중 151~175

교육 기관: Emanuele G

Nov 14, 2019

Excellent course

교육 기관: Lalit S

Jan 29, 2019

Awesome

교육 기관: Kristin A

Jan 30, 2019

A good intro to NLTK and text mining in Python, though sometimes the effort put in to render an assignment acceptable to the autograder was a headache.

교육 기관: Utkarsh T

Dec 18, 2018

NA

교육 기관: CaitlinYao

Feb 17, 2019

The assignments are much harder than the slides, which means much more self-learning is required.

교육 기관: Muhammad S J

Mar 08, 2019

Overall course is very usefull for me. But there is lot of detail is missing in week 4. Wordnet and Gensim usage, Detail about the LDA and semantic similarity. I hope next time there is separate video lecture for detailed about Semantic simalarity.

교육 기관: Roberto L L

Mar 01, 2019

This an excellent course to open a door for NLP, an exciting topic.

교육 기관: Michael M

Mar 22, 2019

Great course. Auto graders have some issues.

교육 기관: Christian E

Mar 27, 2019

Very good content

교육 기관: Darius T

Apr 02, 2019

The course material is good. The main issue with this course are some of the assignments, which are pretty complicated, are not explained well enough and sometimes don't even test the knowledge of understanding text mining.

교육 기관: Lucas S R

Feb 08, 2019

The course presented a good content for beginners in NLP and I feel confident to start using what I learned in my work. But, the grader for the assignments is too slow and buggy, this should be fixed so new learners don't feel frustrated. In addition, for assignment 4, the lda trainning parameters are not viable for trainning in coursera's environment, it should be reviewed.

교육 기관: Alexander G

Jan 13, 2019

It would help to connect the teaching better to the assignments. Especially in Week 4 there is to little connection. There is not even a course notebook to practice some of the material.

교육 기관: Ayush A

Jul 14, 2018

The course was good, but as I progressed in the course, the approach for code began slackening off, as it felt to me. Topics are discussed well, but the implementation in code was something that took a star away.

교육 기관: Archit A

Jul 11, 2018

Course content has to be modified, the instructor has to more in depth in some of the topics especially the final week topics. Rest apart, I enjoyed the course, the assignments and quizzes are of optimal length and difficulty. Thanks for making this course!

교육 기관: Aditya h

Jul 09, 2018

Great course! very much handy if you are looking for a 'Text processing in Python' primer. The good thing about the course is that it explains the libraries. For example - NLTK vs SciPy for applying ML on text. What's missing, is the Deep Learning aspects of text processing

교육 기관: Beda K

Aug 27, 2017

Good introduction into the field of text mining, but very brief. I think the structure could do with some fine tuning as for example the extraction of features from text is left mostly untouched or is covered by the home work only. All in all I found it slightly less well structured than the previous parts in the series, but it was still very useful and helpful as a starting point.

교육 기관: Srinivas K R

Sep 16, 2017

A good course which introduces you to the basics of text processing and text mining in python and exposes you to tools such as regex, nltk and gensim. While the lectures and assignments do promote this learning, a lot of the criticism that is directed at the course is due to the auto-grader issues. You can easily side-step a lot of these problems by going through the forums. However, I do think that the course could have been better planned and executed, even IF the only purpose is applied text mining for e.g., better context and some exposure to theory or at least pointers to where more material could be found for self-study would have been helpful. However, I did learn some things from the class giving me a push towards learning more on the subject on my own.

교육 기관: Pankaj K

Jan 07, 2018

Great material with practical applications! I utilized a lot from this course in my work! I think the assignments should be made a little bit more clearer, specially the first one. Took a lot of time to do the first one, due to some exceptions that were not mentioned in the exercise, at least one should mention that there might be cases other than specified here.

Overall a great course! Thanks!

교육 기관: Mauro G

Oct 03, 2017

The lectures are in my opinion too concise. The programming assignments are very interesting. Perhaps the week 1 programming assignment is too complex.

교육 기관: Abe G V T S

Oct 05, 2017

The class was great. However the assignments had a lot of problems.

교육 기관: Yang F

Aug 23, 2017

Useful topic.

교육 기관: Charles F

Sep 20, 2017

The course content is very interesting and high quality; however, the video slides include code that is not available in e.g. jupyter notebooks. Also, the assignment markers do not give any useful feedback - more than half of the time spent was usually when 99% of the task was complete but some very minor detail threw the marker off.

교육 기관: Han C

Sep 01, 2017

Learned lots of new stuff, but some details are not established well including autograder issue at the last assignment. Hope this gets cleared out soon.

교육 기관: Carl W S

Sep 01, 2017

Overall, a solid course, though it felt a bit like a face-to-face lecture course recorded to video. The material was helpful and well-explained, but I feel it could benefit from taking advantage of the MOOC medium more effectively, such as by providing code sample notebooks for the students to run and modify, which have been very helpful to me in understanding the material in other courses in the same specialization.

교육 기관: Aditya R

Oct 05, 2017

Good Course