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Avis et commentaires pour d'étudiants pour Applied Text Mining in Python par Université du Michigan

3,659 évaluations

À propos du cours

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....

Meilleurs avis


26 août 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!


4 déc. 2020

Excellent course to get started with text mining and NLP with Python. The course goes over the most essential elements involved with dealing with free text. Definitely worth the time I spent on it.

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76 - 100 sur 705 Avis pour Applied Text Mining in Python

par Lucas G

16 août 2017

Good Course! The expected format for the assignment answers is often a little bit too finicky, but with careful reading of the prompts, they are all doable, and the tasks themselves are fun and useful.

par Jeremy R

5 déc. 2020

Excellent course to get started with text mining and NLP with Python. The course goes over the most essential elements involved with dealing with free text. Definitely worth the time I spent on it.

par Tony K

23 juin 2020

Everything was awesome, assignment 2 was my favorite in a long while in this specialization series. Week 4 was a little weak, and felt rushed. Overall, I enjoyed this course 4 of the 5.

par Max S

26 mai 2020

The course is great, but I would suggest some contact with the issues and problems faced. Some parts of the exercises are advanced for those who have never had contact with the subject.

par Diego F G L

15 mars 2021

La variedad de temas del curso lo hace un curso muy recomendable. El nivel de las tareas está de acuerdo a lo que se enseña. Muy recomendado como un primer acercamiento al tema.

par Punam P

20 avr. 2020

Nice experience..Thanks to Resp.Professor for clear the concepts so deeply and enhancing the knowledge in right path..Niceever and helpful course..Thanks to team & university..

par Manuel A

8 sept. 2018

Just enough theory and an comprehensive guide through regex, nltk and some features from gensim (LDA). Assignmets are very challenging and some nice utilities are developed.

par Fernando M

15 août 2020

It was a great course, I am really enjoying this specializtion. Even it is a great course, I think the previous in the specialization were better, maybe i like them more.

par Sonu C

5 juil. 2018

Great course, very well balanced pace of learning. Adds good amount of working knowledge with NLP tools; definitely not covers everything but more than what I expected.

par Chung-Han L

23 mai 2020

I like this course, even though it adopts auto-grader instead of peer-grading. It requires more accurate of your code and more skill of programming, but it is worthy.

par Sales A

1 août 2019

A lot of self-learning. The assignment is challenging, but well designed! The forum is the key to understand the Computer science writing style in the assignment :)

par Sarah H H

20 mai 2019

Loved this course. the pacing, the instruction. it flowed and I felt i could execute what I learned without too much head scratching due 'missing leaps of info'.

par Andrii T

7 août 2020

Just the right proportion of theory and practice. This course isn't enough to even study basics of text mining, but it has relevant materials to start from.

par Ayanabha G

12 juin 2020

Feeling very proud of you Vinod sir ! I am from India and your this beautiful Indian accent and relatable examples helped me to understand things easily :)

par Ari W R

1 sept. 2020

This is so clearly information about text mining. I get more information from this course. I hope can implemented this knowledge for the real world cases.

par David K

17 janv. 2020

An interesting topic that takes text mining to a new level, it was really insightful to understand how these tools can be applied to the real world.

par Sayed S S

21 avr. 2020

An amazing course.I love how even the basics are covered and its transition to the difficult topics. An amazing explanation with a very right pace.

par Ritesh S

9 juin 2020

It was an excellent course to get insights of python concepts with text mining and to learn much more new advance things in python. Thanks A lot.


16 juin 2020

Course was really good and the the way mentor was teaching us the concept was really good. For me the best course so far in this specialization.

par Arslan M

25 juin 2021

Assignments were tough and involved a lot of searching through the internet. Many things remain unexplained, it could have had more detail.

par Aya

17 déc. 2018

This instructor was great! His slides and explanations were much easier to follow than the other course instructors in the specialization.

par Vladimir

5 déc. 2017

Highly recommended course about text mining and modelling for Computer Scientists! Great and challenging assignments to grasp the skills!

par Gerardo M C

11 nov. 2017

Nice and interesting course. This course opens a lot of possibilities to processing information data and bibliometric studies.

par Arunbh Y

6 nov. 2021

The course is good but the packages and methodology needs to be changed in accordance with the current version of the python.

par kaushal

25 mai 2019

it's great course to learn text mining in python , you will find many good examples which are related to real worlds problems