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Applied Text Mining in Python, Мичиганский университет

Оценки: 1,623
Рецензии: 301

Об этом курсе

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....

Лучшие рецензии

автор: 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.

автор: SC

Jul 05, 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.

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Рецензии: 293

автор: Parul Sharma

Apr 20, 2019


автор: 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.

автор: Matt Kershner

Apr 17, 2019

The overall material was good. That being said, this is the first time I have taken a MOOC course and felt like 90% of the time I spent was fighting with the auto grader. The instructions in many instances were unclear, so when you are dealing with a grading system that grades items as 100% correct, vs 100% incorrect with really no feedback as to what you did wrong it can be very frustrating. Without the Discussion forums there is no way I would have ever figured out what to do for some parts of assignments.

автор: Ana Maria Lopez Moreno

Apr 15, 2019

Excellent course

автор: Keary Parinis

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.

автор: Greg Schwartz

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.

автор: Darius Tamašauskas

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.

автор: Esmerlin Rosario Moya

Apr 01, 2019

Sin desperdicios

автор: Samuel Eduardo Gonzalez Garcia

Apr 01, 2019

great teacher!!

автор: Yunfeng Hu

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.