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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

4.5
396 個評分
57 條評論

課程概述

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....

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JQ
2020年7月1日

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.

AY
2020年5月19日

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

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

創建者 Md. M H

2020年7月17日

nice course

創建者 Suraj

2020年6月10日

thank you!

創建者 Kamlesh C

2020年6月27日

Thank you

創建者 Suraj Y

2020年6月1日

very good

創建者 MD M A

2020年6月20日

goog

創建者 Vajinepalli s s

2020年6月20日

nice

創建者 tale p

2020年6月16日

good

創建者 purnachand k

2020年5月12日

Good

創建者 Tanzim M

2020年4月9日

nice

創建者 Devsmita P

2020年8月24日

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

2020年6月4日

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

2020年8月2日

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

2020年5月27日

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

創建者 Aniket D

2020年6月6日

It was quite good and handy!

Just apt, and not much difficult!

I enjoyed learning it!

Thanks a lot!✌

創建者 srinivas d

2020年6月8日

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

創建者 Bhanu T G

2020年5月26日

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

創建者 Sourav K

2020年6月5日

Offline work could be better than cloud desktop

創建者 Manoj K B

2020年5月15日

buffers in the end modules

創建者 K Y

2020年5月29日

Informative for beginners

創建者 usha

2020年5月18日

Clear explanation.

創建者 PUBALI M

2020年5月5日

nice

創建者 Gurpreet S C

2020年4月19日

Good

創建者 Brijesh G

2020年6月10日

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

2020年6月2日

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

2020年7月17日

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