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미시건 대학교의 Applied Text Mining in Python 학습자 리뷰 및 피드백

3,156개의 평가
596개의 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


Aug 27, 2017

Quite challenging but also quite a sense of accomplishment when you finish the course. I learned a lot and think this was the course I preferred of the entire specialization. I highly recommend it!


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. :-)

필터링 기준:

Applied Text Mining in Python의 588개 리뷰 중 26~50

교육 기관: G B K

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. :-)

교육 기관: Ben K

Jun 26, 2018

Would love to see these courses have more practice questions in each weeks lesson. Would be helpful for repetition sake, and learning vs only doing each question once in the assignments.

교육 기관: atul s

Jun 11, 2020

Course needs to be taught better. Assignments were way too difficult. Usually this happened in 1 out of the 4 weeks in all the previous courses of this specialisation. This course had all assignments having students do lots of searching online and the forums. Other learners comments turned out to be a lifesaver. This should not be the case for the entire course.

교육 기관: Carlos F P

Oct 03, 2019

Autograder is a disadvantage that sometimes can take many hours to figure out. Also, this course was a let down compared to the previous in the specialization. I wish there were more examples.

교육 기관: Moustafa A S

Aug 10, 2020

the materials are out dated like hell, but meh at least i got the basics

교육 기관: Jun-Hoe L

Sep 06, 2020

Initially the lectures started fine. But by week 2, there is a big gap between the level of lecturers/material which are too superficial and the assignment which are very detailed. 90% of the time doing the assignments consist of looking up the forums or stackoverflow. The autograder is also severely outdated, never been updated for the past 3 years since the start of the course. Week 3 itself the autograder requires some "wrong answer" to pass, and this has never been updated. The mentors in the forum especially Uwe is helpful, but he's only patching the leaks by providing guides on passing the autograder. I'm only taking this course to finish the specialization, but I would not recommend this course at all, especially since it's paid and I feel it's not worth the price for the outdated content.

교육 기관: Christopher M W

Aug 12, 2020

This course seemed much less useful than the other Python for Data Science courses:

1.) Too many topics addressed at surface level, instead suggest be more selective and go deeper in playing around with a smaller number of techniques/models

2.) The coding assignments felt very rote/mechanical, mostly I think was a tradeoff to try to touch too many individual techniques/models. Would have preferred assignments more like - try to achieve X practical objective (good classifier score, etc) in whatever way you think makes sense, playing with or looping through parameters of the techniques/models to get there

3.) There were a number of ambiguities and inaccuracies in the assignments that wasted a considerable amount of time for not just me but a lot of people - see the forums

교육 기관: Sudhakant P

Jun 03, 2020

Week 2 and Week 3 are OK. But Week 1 and Week 4 are Horrible. All the other courses in this specialization are amazing. But this one, I don't think so. If you really want to learn NLP, go for other sources. This course is just like a revision for the ones who are already pretty good with NLP.

교육 기관: Vladimir V

Aug 14, 2017

A complete waste of time. You are better off Googling the concepts as the explanations are absolutely inadequate. The homework is nice and challenging but the material covered in the lectures does not prepare you to complete it. You are pretty much on your own. Too bad that you need to take this course to complete the specialization. Definitely not worth the $80. Very disappointed!!!!

교육 기관: Markus M

Sep 24, 2017

One of the worst courses I have ever attended. The subject is treated on the surface.

The exercises are sometimes not covered in the lectures. The auto-grader is badly configured.

It was annoying and frustrating to do the exercises. Sometimes an untold oderering of the results was expected. Sometimes an untold normalization has to be done.

교육 기관: Nathan R

Oct 17, 2017

The professor is wooden. The quizzes are ridiculously easy. The programming assignments nearly impossible. Beware the hidden workings of the auto-grader. If you're very lucky, one of the other students will prompt the TAs to action in the forums. This is, by far, the worst course in this specialization.

교육 기관: Will W

Aug 23, 2017

Honestly, I was pretty disappointed in this course. Assignments consistently took much longer than indicated, in large part because of recurrent problems with the autograder and unspecified requirements in assignment instructions.

교육 기관: RAUL E G

Apr 13, 2018

The professor needs to prepare students better for exams and assigments. Too few lectures.

교육 기관: Xing W

Oct 28, 2017

The video is still in python 2. Very limited instructions.

교육 기관: Benjamin C

Aug 05, 2020

I was expecting to learn at least something

교육 기관: Aziz J

Dec 18, 2017

This class was fantastic. It was an order of magnitude times better than the previous course, 'Applied Machine Learning,' by Kevyn Collins-Thompson. Professor V. G. Vinod Vydiswaran started most lectures with a purpose and an alluring example. He spent a good amount of time building intuition behind the algorithms and techniques involved, and saved most of the coding for challenging and satisfying homework assignments--all qualities that the previous course did not have.

Finally, professor V. G. Vinod Vydiswaran was simply energetic about teaching. I didn't have to change playrate to > 1.2x. I genuinely enjoyed his teaching style.

This course has restored my faith in the 'Applied Data Science with Python' specialization by University of Michigan and I am confident in my ability solve text classification problems in Python. Highly recommended, along with the first two courses in this specialization.

교육 기관: Vaibhav S

Jun 26, 2018

I never knew, that the data that is present over the internet can provide such fascinating details, from which we can infer a lot. The teaching methodology of Professor Vinod where he introduces to the very basic concepts of this course, and then slowly and steadily moves to some of the core concepts of NLP is really fantastic. This course gives you all the key ingredients you need to create advanced NLP projects using python programming language.

교육 기관: Yusuf E

Apr 18, 2018

Very good overview of the NLP tasks. The assignments were again really challenging and required a lot of navigating the documentation and forums. The autograder is really frustrating sometimes though especially when it can't upload your file and you miss that part and change your correct code. Again, the assignments are really difficult without help from the forums but it was worth it.

교육 기관: Kedar J

Nov 09, 2018

Great course! The assignments were at times hard to understand. Thanks to the wonderful support from the fellow students and mentors in the discussion forums, you will get most of the clarifications. Would recommend completing first 3 courses of this specialization before this one. There are a plenty of new concepts and new libraries introduced in this course.

교육 기관: Milan B

May 08, 2020

I have been really interested in text mining for his wide applications. This course is very nice, it gives all the bases to deal with text mining problems! However, there could have been a Jupyther Notebook to put in applications the bases with Python about Topic Modeling in order to be more confortable for the Assignement 4.

교육 기관: Yunfeng H

Mar 27, 2019

This is a very helpful courses for text mining. It starts with cleaning data and then gradually build up the skills to classify and group texts. I love all the case studies. The assistant walks me through the tasks using the tools and methodologies mentioned in the lectures. It also helps to solve the assignments.

교육 기관: Daniel N

Sep 07, 2017

I enjoyed the course and have found the topics very interesting. One criticism is that the general quality of notebooks provided with example codes wasn't as high as for other courses in the specialization.However the lecturer was really nice and gave very good explanations even for complicated concepts.

교육 기관: Γεώργιος Κ

Apr 24, 2018

The lessons are useful, and all of the knowledge is a must have. Some things could go deeper, some needed more explanation. As a result this is a must have course for text mining but I think that the level is introductory and in real world one must have more skills to perform a respected text mining.

교육 기관: Jan Z

Sep 07, 2018

Great course overall. I have learned a lot, but last week had no tutorial example covering the topic and w4 assignment was not literally described resulting in spending a huge amount of time on trying which possible solutions will be accepted by autograder. Discussion forum helped a lot though.

교육 기관: Víctor L

Feb 14, 2018

An excellent course, it gives a full introduction to text mining, what it is useful for, covers different techniques, provides challenging activities. Maybe it lacks of a practical activity in Week 4 before the assessment, but overall the course has very good content and an excellent instructor