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Learner Reviews & Feedback for NLP: Twitter Sentiment Analysis by Coursera Project Network

4.6
stars
337 ratings

About the Course

In this hands-on project, we will train a Naive Bayes classifier to predict sentiment from thousands of Twitter tweets. This project could be practically used by any company with social media presence to automatically predict customer's sentiment (i.e.: whether their customers are happy or not). The process could be done automatically without having humans manually review thousands of tweets and customer reviews. Note: 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....

Top reviews

YP

Jul 7, 2020

This was amazing. I started to worried, because I think that train an ML is too complicated but this guided project show me that this is something that anyone need to learn. Thanks a lot!

SS

Sep 16, 2020

Overall nicely guided small project. The tutor explained it very well. Please make more such short courses. More concepts from Basic NLP can be covered.

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1 - 25 of 65 Reviews for NLP: Twitter Sentiment Analysis

By Phan C N

Sep 4, 2021

The project teach here is very basic. 70% of the content is simple python command. The algorithm here is also very simple without any guidance on how to improve. The dataset is also very simple as well.

Some of the code are not optimal, use too many for loop and you can't really use it with real dataset because it will take a very long time.

This is fun for intro into NLP but you can't show this as a "project" to anyone, because it's really basic and simple.

By Aniruthaan

Jul 26, 2020

Good one for basics ! Download File Not Available

By Dương V B

Aug 19, 2020

This guided project is a chance to learn a basic technical skill in data cleaning. I love the explanation for Naive Bayes algorithm.

By Supamas N

Sep 23, 2022

First of all, I would say the instructor is really great in explaination and project guidance. In overall, the project is fantastic and easy to follow. However, I found some obstacles that made me follow the project pretty much slower than I expected. I wish someone who responsible for this course could see my comment and improve these.

1. Project was performed on Python which was installed on a server and we work through the Cloud Workspace which is great because we don't need to install any software on our computer. However, the default folder did not set to the working folder. For those who are not familiar with Python, this might be the first big problem.

2. The first and most important thing is the data collection. In the project we have two ready-to-use datasets. Again, for the beginners, we don't know how to get the data and how to rate them 0 or 1. Reality, we could not analyte further if we couldn't get the proper dataset. So, this course will give us more benefit if it shows us how to grab the data and how to rate 0 or 1 on the posiitive/negative comments. If there is another lesson about this, you should inform us to take that course prior taking this one.

3. Cloud Workspace is always unstable and then it works quite slow, especially when we need to scroll up/down.

Again, I appreciated the course in overall, but I suggested it need some improvement. Less stars might make the instructor pay more attention on the comment. Thank you.

Sincerely yours,

By Ayush G

Sep 25, 2020

rhyme is too annoying, it is too slow. Also, the dataset and code are not provided in the end this is disappointing.

By Peter H

Feb 22, 2021

The online tool is a true pain

By Juan P S G

Jul 19, 2020

El concepto tras este tipo de cursos está demasiado bien. El curso es completo y deja bases para aplicación en proyectos fáciles. Buen curso para empezar a buscar motivación en este tipo de temáticas.

By Yomira G P

Jul 8, 2020

This was amazing. I started to worried, because I think that train an ML is too complicated but this guided project show me that this is something that anyone need to learn. Thanks a lot!

By SUMIT S

Sep 17, 2020

Overall nicely guided small project. The tutor explained it very well. Please make more such short courses. More concepts from Basic NLP can be covered.

By Aashirbad

Jul 27, 2020

MemoryError: Unable to allocate 9.03 GiB for an array with shape (25569, 47386) and data type int64

Solve the issue

By Akshay H

Sep 29, 2020

The course was good. The instructor covered topics pretty well in the beginning part but kinda rushed at the end. The rhyme virtual machine was terrible. It was too laggy and I haven't been able to practice code snippets in it. Had to write code in Jupyter Notebook on my computer.

By Leonardo S

Jan 29, 2021

Many bugs, project cannot be downloaded

By Jeremy D

Jan 29, 2021

I definitely enjoyed this project. Ryan explained everything very clearly as the content became progressively more complex towards the end of the course. He broke down the code piece by piece so that you could actually understand what every line of code was doing and its importance to the project. Thanks so much!

By Olivia G

Jul 30, 2021

I'm a linguistic student who's considering doing several NLP project. I was so daunted by so many lines of codes and those technical terms that I couldn't bring myself to code. But after doing this project I'm not that afraid anymore. Thanks! Look forward to more immediate level NLP projects.

By R S K

Feb 12, 2021

A good introduction to NLP using sklearn. A lot more could have been done with the data but since the data set is available on Kaggle, one should probably explore it more after this project. Overall, good instruction and project.

By Shashi K S

Oct 14, 2020

The course content was very awesome and the way the instructor taught me was really good, it felt like we were sitting face to face. The pipeline was broken down into simpler steps which eventually led to a better understanding.

By Suhaimi C

Feb 24, 2021

Great guided project. Instructor is very patient explaining the terms and concepts. Enjoyed learning this course. Highly recommend if you would like to learn machine learning using python on how to analyze twitter sentiments.

By Kanaparthi J S | A

Aug 20, 2020

This project gives us a good idea about data analysis and if any one is using google co lab and when you are running naive Bayes algorithm and you got out of ram problem then just decrease the size of the data set to 25000

By YOGESH K P

Sep 27, 2020

I would love to do more project under the guidance of the this professor.

Each and every concept was clearly explained

Thank You

By Andrei C

Feb 23, 2021

I liked the way the instructor explained how the Naive Bayes classifier works. It was the best explanation I have seen so far

By Cheikh B

Mar 4, 2021

Very good project and very good explaination you make difficult things easier to understand thank you Ryan Ahmed

By Nevcihan t

Sep 26, 2020

It is really helpfull project that covers almost all steps of sentiment analysis. Thank you.

By SHEKHAR S

Aug 23, 2020

This project is really useful and i enjoyed learning many new concepts from this project.

By Saurabh T

Jul 23, 2022

Great course ! Detailed explanation of concetps and code was given by the instructor.

By tanushree p

Sep 16, 2020

Awesome course. The instructor is awesome in explaining all the details very well