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Opiniones y comentarios de aprendices correspondientes a Applied Text Mining in Python por parte de Universidad de Míchigan

2,985 calificaciones
572 revisiones

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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....

Principales revisiones


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. :-)

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26 - 50 de 565 revisiones para Applied Text Mining in Python

por 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.

por Nills F

Jul 17, 2020

I finished this course because I already finished 3 out of 5 courses in the total data science specialization. If you're just doing this course, I wouldn't recommend it. It's very heavy on theory, and the practical elements of Python are only touched upon slightly. Expect to spend a lot of time googling the answer to the weekly assignments, and reading through the forums of the course to find which slight edit you'll have to make to make it work. Oh, and the course instructors/teaching assistants are nowhere to be seen in the forum. There's been errors in the course itself and in the auto-grader that were reported 3 years ago that still aren't fixed.

por 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!!!!

por 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.

por 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.

por 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.

por RAUL E G

Apr 13, 2018

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

por Xing W

Oct 28, 2017

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

por 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.

por 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.

por 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.

por 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.

por 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.

por 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.

por 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.

por 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.

por 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.

por 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

por Brian L

Oct 19, 2017

Great course! I have been doing some text mining in another tool, and I learned some useful things that I was able to put to use almost immediately ... now that I have the data science part in hand, I just need to figure out some Python details in order to format my output for my client.

por Davide T

Aug 18, 2017

Great teacher, great course. Topics are very interesting and well explained, assignments' difficult is just right. I'm sure they will put this review in some kind of sparse matrix in order to train a classifier and make previsions for future it is a must-join course!

por Praveen R

Dec 10, 2019

I learnt about NLTK package and its capabilities. It was good to know how to build vocabulary and guess missing words and match sentences lemmatizing them. Good eye opener course. There is way much more to be learnt in this subject. This is just an introduction (a good one).

por David R

May 17, 2018

When looking at the full course in coursera, I was thinking that would be the course which would interest me the least, but at it turned out, now I'm really interested in text mining, and I'm planning to read more publication to understand that field

por Binil K

Aug 15, 2017

This is a fantastic course though you might find some trouble with the grading part (Auto grading). This course will give you a good understanding about the various most useful techniques in text mining. Course is well structured and really helpful


May 12, 2019

Well-taught course, I'd been struggling with regular expressions, thank you for simplifying the concept; additionally, you've opened my eyes to an entirely new world of data science for which I can think of an immediate productive application. :-)

por BrajKishore P

Jan 30, 2020

The overall course was well designed, all lectures were arranged in a proper sequence and all the slides and jupyter notebooks were good covering all the aspects, but I felt some difficulties in the 2nd week in POS tag, overall it was too good.