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學生對 Coursera Project Network 提供的 Perform Sentiment Analysis with scikit-learn 的評價和反饋

382 個評分
57 條評論


In this project-based course, you will learn the fundamentals of sentiment analysis, and build a logistic regression model to classify movie reviews as either positive or negative. We will use the popular IMDB data set. Our goal is to use a simple logistic regression estimator from scikit-learn for document classification. This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with Python, Jupyter, and scikit-learn pre-installed. Notes: - You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want. - This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions....



Jul 02, 2020

This project is very useful for people that don't know anything about sentiment analysis and it's approach with Scikitlearn, like me. It's very introductory.


May 20, 2020

Very well designed course. Starting from the beginning of text pre-processing till evaluation of model, all steps are explained and implemented very well.


26 - Perform Sentiment Analysis with scikit-learn 的 50 個評論(共 56 個)

創建者 Md. M H 1

Jul 17, 2020

nice course

創建者 Suraj

Jun 10, 2020

thank you!

創建者 Kamlesh C

Jun 27, 2020

Thank you

創建者 Suraj Y

Jun 01, 2020

very good

創建者 MD M A

Jun 21, 2020


創建者 Vajinepalli s s

Jun 20, 2020


創建者 tale p

Jun 16, 2020


創建者 purnachand k

May 12, 2020


創建者 Tanzim M

Apr 09, 2020


創建者 Devsmita P

Aug 24, 2020

This course is Just fine and the required material to gain knowledge about hands-on Sentiment analysis as well as some machine learning models. I can across various models. The course also provides you websites related to some packages like NumPy, Matplotlib and Scikit-learn, you could 1st go through and then start the course for understanding it better. Hence, I would recommend others go through this course.

創建者 Gopi K

Jun 04, 2020

Guided Project should be longer may be of 3-4 hours and consists of real world industry problem. It would be beneficial fo bachelors students.

創建者 Dennis W

Aug 02, 2020

Easy to follow with simple instructions. Excellent introduction to text mining using TF-iDF and combine with simple machine learning.

創建者 Justice A

May 27, 2020

This is a good project with well explained concept, it has help me remember things I have forgotten

創建者 Aniket D

Jun 06, 2020

It was quite good and handy!

Just apt, and not much difficult!

I enjoyed learning it!

Thanks a lot!✌

創建者 srinivas d

Jun 08, 2020

It would be good if we explain some terms in detail like tf-idf, count vectorizer, porter etc

創建者 Bhanu T G

May 27, 2020

It'll be better if access time for cloud desktop is not limited.

創建者 Sourav K

Jun 05, 2020

Offline work could be better than cloud desktop

創建者 Manoj K B

May 15, 2020

buffers in the end modules

創建者 K Y

May 29, 2020

Informative for beginners

創建者 usha

May 18, 2020

Clear explanation.


May 05, 2020


創建者 Gurpreet S C

Apr 19, 2020


創建者 Brijesh G

Jun 10, 2020

More explanation is needed.

Pre-requisites were not mentioned.

Explanations needs to be more cleared.

Project is costly if compared to the content. Youtube has same content in free.

創建者 Malki W

Jun 02, 2020

The practical session wasn't available. Forever connecting. But the videos are good. And glad the instructor has uploaded the notebook in resources

創建者 Cesar K K

Jul 17, 2020

As a project, I was expecting a practical use. It looks like a simple exercise