Good one for basics ! Download File Not Available

T​he 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.

S​ome 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.

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

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

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

The online tool is a true pain

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.

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!

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.

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

Solve the issue

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.

Many bugs, project cannot be downloaded

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!

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.

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.

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.

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.

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

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

Each and every concept was clearly explained

Thank You

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

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

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

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

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

Well explained.

Person with less knowledge can also go for this course.

Thank you

Great course for beginners. Well explained. And screen split was very handy.