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Opiniones y comentarios de aprendices correspondientes a Perform Sentiment Analysis with scikit-learn por parte de Coursera Project Network

406 calificaciones

Acerca del Curso

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....

Principales reseñas


1 de jul. de 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.


19 de may. de 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.

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26 - 50 de 56 revisiones para Perform Sentiment Analysis with scikit-learn

por Widhi A P

14 de jul. de 2020

Very good Course


9 de sep. de 2020

very useful!

por Manan B

26 de may. de 2020

Great Course

por Md. M H

17 de jul. de 2020

nice course

por Suraj

10 de jun. de 2020

thank you!

por Kamlesh C

27 de jun. de 2020

Thank you

por Suraj Y

1 de jun. de 2020

very good

por MD M A

20 de jun. de 2020


por Vajinepalli s s

20 de jun. de 2020


por tale p

16 de jun. de 2020


por purnachand k

12 de may. de 2020



9 de abr. de 2020


por Devsmita P

24 de ago. de 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.

por Gopi K

4 de jun. de 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.

por Dennis W

2 de ago. de 2020

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

por Justice A

27 de may. de 2020

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

por Aniket D

6 de jun. de 2020

It was quite good and handy!

Just apt, and not much difficult!

I enjoyed learning it!

Thanks a lot!✌

por srinivas d

8 de jun. de 2020

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

por Bhanu T G

27 de may. de 2020

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

por Sourav K

5 de jun. de 2020

Offline work could be better than cloud desktop

por Manoj K

15 de may. de 2020

buffers in the end modules

por K Y

29 de may. de 2020

Informative for beginners

por usha

18 de may. de 2020

Clear explanation.


5 de may. de 2020


por Gurpreet S C

19 de abr. de 2020