Ratings and Reviews for Applied Text Mining in Python

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.

G

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

This course did cover some good topics (Naive Bayes model, similarity, part of speech tagging). However, I felt the homework was more about manipulating Python data structures than learning anything significant about text mining. Some of the theory behind the models was covered, but didn't make it to the homework. It would be difficult since this is a short class, but I would have preferred more about tips on which model to use and feature engineering / selection, and examples of practical applications of text mining. (Or stories of failures in the instructors' experience!)

Excellent, but really hard to finish!

A lot of issues with the auto graders

Great teaching material and clear explanations. I learnt a lot. Nevertheless the assignments auto-grading tool is awful. I spent more time looking for the necessary hacks to pass the assignments than working on text mining.

Covers a lot of things in breath, but it could have been a bit longer!!

Week 4 was not sufficient

A bit lack of coherence in theory. Sometimes, the theory needed for the assignments was not given with enough detail, and you had to browse the forums for the information, and applying it to your assignment just to pass, sometimes without understanding why you were doing what you were doing. More Python examples needed. For week 3, the tutorial about recommender systems was perfect for the assignment.