Chevron Left
Applied Text Mining in Python(으)로 돌아가기

미시건 대학교의 Applied Text Mining in Python 학습자 리뷰 및 피드백

4.2
2,412개의 평가
456개의 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

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.

필터링 기준:

Applied Text Mining in Python의 448개 리뷰 중 201~225

교육 기관: YOGESH K M

Sep 01, 2018

I am a Self Driving Car Engineer, I have worked with deep learning but i wanted to know about Machine Learning So i was exploring here. I am new to Text mining and not interested much, but it was worth exploring and to to know potential of Test Mining. Course was very well summed up for me as a this is new for me. Content was good enough to start and hit some practical questions.

교육 기관: 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.

교육 기관: Charles F

Sep 20, 2017

The course content is very interesting and high quality; however, the video slides include code that is not available in e.g. jupyter notebooks. Also, the assignment markers do not give any useful feedback - more than half of the time spent was usually when 99% of the task was complete but some very minor detail threw the marker off.

교육 기관: Чижов В Б

Dec 18, 2017

It is interesting, cognitive and very useful. But, there were very few answers from the teaching staff in the discussions at the forum. In previous courses of this and other specializations, the teaching staff took an active part in the forum and this greatly helped in understanding and fulfilling the tasks of the course.

교육 기관: Vidya M S

Sep 30, 2019

A good brief introduction to test mining with python. The professor attempts to explain the topics well. Good rigor of the assignments. How ever for the last module , absence of explaination with a notebook is strongly felt as the concepts get deeper in understanding and woud have helped with the last assignment.

교육 기관: Keary P

Apr 14, 2019

Good intro into NLP and NLTK. Assignments provided great hands on practice with NLTK, SciKit Learn and regular expressions. Could use additional materials for key concepts such as sentiment analysis and ngrams. Could also use a more real world case study for the final project.

교육 기관: Aditya h

Jul 09, 2018

Great course! very much handy if you are looking for a 'Text processing in Python' primer. The good thing about the course is that it explains the libraries. For example - NLTK vs SciPy for applying ML on text. What's missing, is the Deep Learning aspects of text processing

교육 기관: Archit A

Jul 11, 2018

Course content has to be modified, the instructor has to more in depth in some of the topics especially the final week topics. Rest apart, I enjoyed the course, the assignments and quizzes are of optimal length and difficulty. Thanks for making this course!

교육 기관: Gunjari B

Jun 18, 2018

Lecture materials are not comprehensive enough to solve the assignments. Course is dependent on precursor courses in the specialization. Assignments often require reference from upcoming weeks. lectures are inadequate. The course is average at its best

교육 기관: Muhammad S J

Mar 08, 2019

Overall course is very usefull for me. But there is lot of detail is missing in week 4. Wordnet and Gensim usage, Detail about the LDA and semantic similarity. I hope next time there is separate video lecture for detailed about Semantic simalarity.

교육 기관: Oscar J O R

Sep 02, 2017

Nice introduction to the topic and interesting tools. The evaluation system could be improved adding more resources focused on the use of the nltk functions or giving some advice about the critical points in the Python demonstrations.

교육 기관: Darius T

Apr 02, 2019

The course material is good. The main issue with this course are some of the assignments, which are pretty complicated, are not explained well enough and sometimes don't even test the knowledge of understanding text mining.

교육 기관: Pushpendra S

Oct 15, 2018

Not well organized. Some of the assignments took way too much time. Instructor's code could have been written out better and could have explained the topics in detail before expecting students to sort through the mess

교육 기관: peyman s

Feb 02, 2020

This course offers a good package of skills with great notebooks (except week 4) and assignments. The videos could be a lot better but mostly understandable. You can always search Youtube for better explained videos.

교육 기관: Ayush A

Jul 14, 2018

The course was good, but as I progressed in the course, the approach for code began slackening off, as it felt to me. Topics are discussed well, but the implementation in code was something that took a star away.

교육 기관: Rushyasrunga K

Jul 20, 2019

Course is great except for the auto grader issues. Please look into the issue. I would like to take this opportunity and thank Prof V. G. Vinod Vydiswaran and all those who helped me to complete it.

교육 기관: João R W S

Aug 23, 2017

Very good course with very good material and teachers. I just missed some more practical examples to follow along the classes, and more further readings (specially for information extraction).

교육 기관: Leo C

Feb 17, 2018

Love the focus on conceptual text processing and practical guides to implementation in python, but the assignment grader was extremely specific for no reason, especially the Week3 assignment.

교육 기관: Alexander G

Jan 13, 2019

It would help to connect the teaching better to the assignments. Especially in Week 4 there is to little connection. There is not even a course notebook to practice some of the material.

교육 기관: Jeremy L

Oct 26, 2017

The course itself is good, but the assigment system is not robust and some sentences are also ambiguous to users. Seeing from the forums, many users get confused in the assigments.

교육 기관: Aswath M

Aug 02, 2019

Excellent course for someone like me who is ambitious and aspires to gain knowledge on new things. The videos can be made bit more elaborate, seems to be rushing towards the end.

교육 기관: Christopher H

Aug 11, 2018

Passionate instructor and a great primer on how software can infer useful data from text. Gives a preliminary understanding on the algorithms used in scikit learn and nltk.

교육 기관: Kangqiao

Nov 04, 2019

A little bit stretched my python skill, but learned a lot. Forum is a good place, and maybe next I will join some study group online or offline to have more discussions.

교육 기관: C-y T

Jan 13, 2020

The course content and the assignments are good. Some descriptions of the assignment questions are ambiguous. The discussion forum is helpful in clarify those issues.

교육 기관: TEJASWI S

Aug 01, 2019

Good course to take although I felt the course could have been better in terms of practice. But overall, would recommend to others if they wish to pursue data analysis.