The course is exceptional in its own way by bringing people to the understanding of probabilistic models. Crisp & Clear. But one need to explore & practise more to gain expertise.

The Viterbi algorithm introduction is a bit hard for us to follow. Probably some writings may help guiding through each steps.

Esta especialización junto con la de Deep Learning se complementan y es son más claros los conceptos y prácticas, gracias!

The tutor sometimes pass the slices too swiftly. I hope that he could wait 2-3 seconds after finishing speaking.

Sone Quiz should also be there. Assignments can be solved by python knowledge an following the instruction

Assignments were incorrect.

Lot of content was squeezed in the last week. Even spread would be ideal

I love the way the instructor teach and the course design which is made to be simple but effective

great material and presentation, there are a few typos here and there but not a big deal

I didn't like weeks 1 and 2 too much but I liked week 3 and I really liked week 4.

I liked the lecture, very well prepared. Only the part on metrics was a bit short

This is a good course but I would like to see more emphasis on the mathematics.

Great course, but the last week felt a bit messy with submission evaluation.

Not sure if it is on purpose, but W4 labs have repeating content.

wonderful course, I learned the fundamental of NLP. Many thanks

T​oo basic and going at too slow a pace

excellent Material & teaching

G​ood, very good.

great course

Veri good

great

good:

* some of the content is well-explained

* provides good solid knowledge about the background and implementation of common NLP tasks

less good:

* notebooks (and content generally) are unevenly distributed

* significantly stronger focus on ML, rather than on the NL side (this is consistent throughout the specialization)

* some of the explanations (e.g. in week 2) aren't clear

* specialization could be structured better -- word embeddings are introduced in course 1, but the in-depth discussion is here in week 4; would perhaps have made more sense to have that content build on itself

In this course, you will learn to build an autocorrect model and different methods of building this model. The course felt a bit rushed with a lack of detailed explanation, students who are familiar with the concepts of NLP from before starting this specialization won't face any problem, but students who had just begun learning NLP through this specialization might feel a little difficult.

Too many gaps in the course. Many concepts not covered in the mathematical sense basic Grad. Desc. math would have been helpful. Also if you want to omit it totally you should have atleast one lab on how one would do it in real life using which library? Pytorch? Keras? What? Rest of the course is okay. Younous is great in explanation.

The course material is good and you can learn new things, you can exercise python skills a lot as the assignments are quite long. However, the tutors are not the best in explaining the material as well as the videos are a bit vague. It would have helped if the tutors were a bit more experienced in teaching, but still overall good!

well I did deep learning specialization earlier things are mathematical, but here they don't go much into maths, and please make some concept chart, to link different algorithms.