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Avis et commentaires pour d'étudiants pour Perform Sentiment Analysis with scikit-learn par Coursera Project Network

4.5
étoiles
317 évaluations
51 avis

À propos du cours

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....

Meilleurs avis

JQ

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.

AY

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.

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1 - 25 sur 51 Avis pour Perform Sentiment Analysis with scikit-learn

par Pranay U

Apr 24, 2020

As a beginner in Data Science, who only knows ML concepts and Exploratory Data Analysis techniques, I really liked this project. I think this project will aid in breaking into the basics of NLP's TF-IDF, bag of words, tokenizer, vectorization concepts.

par Manoj K

May 24, 2020

This course is very helpful if you want to start working with NLP and want to have better understanding of the basics.

par Julio Q

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.

par Anita Y

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.

par ARIMORO, O I

Feb 29, 2020

I love the part that you had to write your codes as the teacher was teaching. It was a great introduction for me to text and sentiment analysis

par Hashan M

Apr 19, 2020

It was really good to practise in a way of a real-world example. Instructor also good. Appreciated the content and the resources as well.

par CLARA T

May 28, 2020

The instructor is very clear and the platform friendly. You can learn at your own pace.

par Mayank S

Apr 22, 2020

I

Liked this course a lot.

Am impressed with conciseness.

Will take other courses too.

par Arzan A

Apr 13, 2020

Had some trouble with the cloud IDE at the beginning, but overall a nice course

par Bishrul H

May 13, 2020

Nicely explained and very good for those who don't have any basics in NLP

par Jalees A

Jun 05, 2020

Very helpful as we are gaining practical knowledge.

par Indrani S

Jun 07, 2020

Course content is good, and easily to understand

par Jaswanth M

Jun 06, 2020

It's really a very good course for a beginner

par Saheli B

Feb 29, 2020

Very interesting and interactive approach .

par Mónica C

Aug 05, 2020

good to start leaning with scikitlearn

par Ronny F

Jul 25, 2020

thanks thats easy understanding

par Galib H K

Apr 25, 2020

Good Explanation! Worth doing.

par MRS. S D A

May 30, 2020

Hands on was very useful

par CHERRY I T

Jul 04, 2020

try it.. and learn

par Gangone R

Jul 03, 2020

very useful course

par Widhi A P

Jul 14, 2020

Very good Course

par Manan B

May 26, 2020

Great Course

par Md. M H

Jul 17, 2020

nice course

par Suraj

Jun 10, 2020

thank you!

par Kamlesh C

Jun 27, 2020

Thank you