Chevron Left
Volver a Applied Text Mining in Python

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

4.2
2,173 calificaciones
411 revisiones

Acerca del Curso

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

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. :-)

BK

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.

Filtrar por:

251 - 275 de 402 revisiones para Applied Text Mining in Python

por Nicolas B

Aug 26, 2017

Great course, could improve the last week with more practical examples.

por Abe G V T S

Oct 05, 2017

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

por Girish G

Nov 20, 2017

Awesome course..It is a good start for NLP. Comprehensively covers all topics. The Autograder for the programming assignment needs

por Henri

Apr 19, 2019

Great course, but expect to spend a lot of time on the assignments because of errors/bugs in the questions/autograder.

por Lalit S

Jan 29, 2019

Awesome

por Utkarsh T

Dec 18, 2018

NA

por 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.

por Christian L

Jul 25, 2019

Good course. Most part of the learning comes from personal work on the assignments (time vastly underestimated)

por Yeifer R C

Nov 25, 2018

Is difficult, but good.

por Avi A

Jan 17, 2019

Great instructor, but the assignments are a big jump from the course notebooks in terms of difficulty. I also faced numerous issues with the autograder. In the last module, there were wrong pieces of code in the notebook and module (like ROC score being calculated from model.predict() instead of model.predict_proba()).

por Daissy D M R

Feb 19, 2019

Good topics and well explanations. A Notebook to support content of week 4 is definitely needed. More explanations in assignment for week 4 is needed. In general, week 4 lacks of organization and good content. that is why I give 3 stars instead of 5

por Mateusz M

Feb 06, 2019

Some of the topics where elaborated very briefly. There was not enough practical examples and instructor was no clear in what he was saying.

por CMC

Feb 11, 2019

I will not say that I did not learn anything. I just wish the autograder was a little better. Basically, quite frustrating to fight a black-box grader. An example of a better autograder is the one implemented by the Princeton people for their algorithm courses.

por Greg S

Apr 13, 2019

I found this course to be a good introduction to NLP. The lectures where fine as such, but lacked in technical focus making it difficult to tie them to the homework. I expect this is the style of the professor. The homework problems where good, but you do need to work to put it together with the lectures.

por Josh C

Mar 14, 2019

The contents are good, but the online autograding system really need to be improved.

por Kartikey S

Jan 05, 2019

Some topics are hastily explained and maybe more content was needed in this course.

por SeyedAlireza K

Dec 23, 2018

I learned some useful stuff in this course but I think it could be a little more deeper and teaching more behind theorems especially for week 4.

por Stephane C

Dec 09, 2018

Week3 and 4. Too much of strange bugs with the auto grader. Not enougth examples...

por Vishal S

Jul 16, 2018

Lectures are good but the assignment of week1 and week 4 is a little bit absurd and unclarified. Autograder is too slow.

por Imran A G

Sep 24, 2018

Good for basic understanding only

por Eric S

Sep 27, 2018

Most assigmets were not in the notes. Still everyhting seems really usefull.

por Raivis J

Aug 11, 2018

Graded assignments need more grounding in practically applicable situations.

por Jeffrey D B

Oct 16, 2018

The course would be significantly improved if there were more hands-on demos during the lectures. Lectures are very high-level and aren't terribly useful when trying to do the lab exercises.

por George M J

Nov 15, 2018

Good content.

Had to spend way too much time fighting the auto-grader.

por pavan b

Nov 19, 2018

good training