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미시건 대학교의 Applied Text Mining in Python 학습자 리뷰 및 피드백

4.2
2,401개의 평가
456개의 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 447개 리뷰 중 426~447

교육 기관: Alex M

Aug 27, 2017

Instructors did a poor job of preparing students for the assignments.

교육 기관: Ji S

Apr 15, 2018

Too coarse, quality worse than other courses in this specialization.

교육 기관: naive666

Jun 29, 2019

Far from expectation, feel upset

교육 기관: Elliot B

Mar 03, 2018

I found this course quite confusing and often unrelated between video lectures and assignments. The lectures maybe covered an assignment in broad strokes but to actually answer any of the questions needed extension research from the student. I felt like I was teaching myself the base content. At that point, what is the point of the lecture videos if they provide no value. I almost stopped my subscription and gave up on the data analysis specialization based on the quality of this specific course. Previous courses in the specialisation did provide useful information in lectures which was then extended upon in the assignments. This method of teaching something in the lectures then building on finessed usage in the assignments is a much better approached.

교육 기관: Christopher I

Mar 14, 2018

The lectures for this course are terribly uninspired, giving very little useful information--the vast majority of it is the professor talking about obvious aspects of language at a very high and useless level. The autograder is frequently breaking for very minor things (such as returning numpy.float instead of float), the questions on the assignments are often misleading, poorly worded, vague, or just generally not very helpful. All in all, this was one of the worst MOOCs I have ever taken, though the Coursera bar is pretty low. It does make me wonder why I bother to pay at all--oh right, Coursera now makes not paying a major inconvenience to course progression.

교육 기관: christopher h

Nov 18, 2017

Compared to other courses in the Applied Machine Learning focus, this is so far the worst. The content and quality are poor. The lecturer is too slow and fails to prepare the student for the assignments. First week is very basic and ends with an assignment in regex. There's plenty of regex resources out there. 2nd week moves forward but finalizes in an assignment that involves concepts not covered in the lecture (ngrams). Weeks 3 and 4 contain too many errors in the lecture and autograder (use of AUC, finding minimum of a sparse array). UofM should rebuild this course.

교육 기관: Prykhodko D

Aug 10, 2019

The course is a joke. Its outdated and not supported, you literally need to spend hours to try and figure and emulate versions used by autograder and even the file structure for files used by default is not accurate and you get file read errors on predefined by them functions on their own virtual environment and need to fix these for them!!! The virtual machine env provided is super slow so need to use your own. Very bad user experience and horrible use of time!

교육 기관: Dr. D W

Aug 27, 2019

What a horrible course. Especially the assignments are such an unbelievable waste of time. Instead of focusing on important concepts and applications, one has to spend hours one "pleasing the autograder" by renaming columns and reading the discussion pages for the correct interpretation of all the ambiguously formulated questions. Very sad! Would be good for everyone if this was removed from the (otherwise great) series "Applied Data Science in Python".

교육 기관: Maximilian W

Feb 14, 2020

Serious sub-par course in the specialisation. The lecturer is good, but sadly the assignments are terrible. Thus the reinforcement - and reliability to problem solving - of the content is poor.

Given the high standard of the first three modules in this specialisation, this is really a shame. I would urge learners to consider whether there is much point in doing this course (other than to get the specialisation completed).

교육 기관: Eduardo C F

Feb 23, 2018

I was under the impression that the course is incomplete, especially week 4, which has no notebook examples of the theory presented. I needed to look at other sites for basic information. I could only complete the exercises because they are easy, otherwise, with the code presented during the course, I would not have been able to. I suggest strengthening the example code in python (see week 3, good code)

교육 기관: Justin M

Sep 14, 2019

Videos are so high-level that they don't help at all understanding the necessary code. Assignments have spelling errors and ambiguity. Week 4 is missing the sample code notebook. I eventually found the sample code notebook in the forums, but this was a big cause of frustrations as I had zero context for how to do the assignment.

교육 기관: Nicholas P

Jul 31, 2019

Unless the instructional staff updates the programming assignments to reflect updates in packages and ensures they can run without additions, do not take this course. It is a terrible reflection on the University of Michigan.

교육 기관: Mark R

Sep 21, 2017

Interesting topic, but a really poor course with barely any content.

Around an hour or less of lectures a week.

I've taken a lot of MOOC's on Coursera and other platforms and this one is poor

교육 기관: Luis d l O

Nov 20, 2017

Too simple. Few information and content, and extremely simple (though with a lot of problems) assignments.

교육 기관: Dario M

Jul 19, 2019

The difficulty of the assignments is in no way related to the simpleness of the lectures.

교육 기관: Akshat S

Mar 26, 2020

The NLTK library was not explained properly. No code explanation was provided.

교육 기관: Jose Á P L

Mar 23, 2019

Este curso no vale para nada, por favor no lo hagais!!!

교육 기관: Vivek G

Dec 02, 2019

Only useful for coarse understanding of the topic.

교육 기관: Feng Q

Oct 04, 2019

totally can't understand the Indian accent.

교육 기관: Mahmoud

Apr 29, 2019

the worst ever I took here in Coursera

교육 기관: Sourav P

Dec 09, 2018

I was not satisfied

교육 기관: Angertdev S

Nov 07, 2019

broken assignments