Superficial descriptions of the topics; quality definitely lacking

No mentors were available or contactable during this course

very superficial

Among the first three courses of the NLP specialization, this is by far the most exciting. I enjoyed very much all the four weeks and the learning syllabus as a whole! Although many complained about the use of trax as a DL framework, I must say, I found fantastic to be able to learn it from people involved in the development! This per se is already an A+. I congratulate the team in taking this decision and pushing this forward. Trax is intuitive and *very* elegant. Chapeau for the devs! If it is as performant as they say for large data sets, this is the future and I am very pleased that the instructors decided to prepare us for it. Apart from all this positive side, I saw in this third course again some content at the end of the assignments that was not introduced during the corresponding week. For example, the Gumbel sampling at the end of Week 2. This was not a graded exercise, therefore it is not a major problem. Nevertheless, it comes out of the blue for the student and it is hard to connect the dots and understand why are we performing this operation at all for the text generation. So, there are a couple of loose threads here and there along the course. But it is a minimal problem. On the other hand, the presentation and discussion of the sequential models in all 4 weeks are very good, again an optimal balance between mathematical formalism, intuition and ease to code. Moreover, the choice of applications in the four week are just right, classification, generation, NER and one shot learning. All in all an awesome package, congratulations!

I recently completed the "Natural Language Processing with Sequence Models" course on Coursera and I must say, it was an incredible learning experience. The course content was very well-organized and easy to follow, with each topic building on the previous one to provide a comprehensive understanding of natural language processing and sequence modeling.

The course instructor, Younes Bensouda Mourri, is a true expert in the field of machine learning and artificial intelligence, and his expertise and passion for the subject matter really shone through in the lectures. He presented the material in a clear and engaging way, and his enthusiasm for the topic was contagious.

The programming assignments were challenging, but not overwhelming, and I found that they really helped to solidify my understanding of the material. The course materials also included interactive quizzes and discussion forums where I was able to connect with other students and learn from their experiences.

Overall, I would highly recommend this course to anyone who is interested in natural language processing and sequence modeling. The course content is top-notch, the instructor is excellent, and the assignments and quizzes provide a great way to reinforce your learning. Whether you are a beginner or an experienced practitioner, this course is a fantastic resource for anyone who wants to learn about NLP and sequence modeling.

The course is expertly designed and provides a comprehensive understanding of the material through a combination of theoretical concepts and practical, hands-on experience. One of the key highlights of the course is the demonstration of the power of sequential models which can outperform probabilistic models that was taught previously and some additional assignments, giving students a deeper understanding of the strengths and limitations of each approach. Overall, the course effectively balances theoretical and practical elements to provide a well-rounded and engaging learning experience.

Great course! I needed to check in on some of the discussions in the discussion forums for this one, so the discussion forums are especially useful (for assignments for weeks 3 and 4). As in the first 2 courses in this specialization, this one also adds most value in its 'lab' and assignment Jupyter notebooks. The videos serve as a gentle introduction to the topics and the concepts from the lectures are emphasized upon in the assignments/labs. Great introductory course overall!

Knowing how things work is very important especially when you deal with Natural Language models. As a professor of modern languages and linguistics, I really enjoy working on mathematical concepts that question the way languages and meaning are construed. In addition, the various practical implementations of the models offered in this course, can be used with very few changes in various kinds of contexts (Education is one of them). Thank you!

Very good course. The only issue I have is when you have some questions about the code or you have issues if no one else has your problem you seem to be on your own. Sometimes I had just some conceptual coding questions and you can't ask why the code is doing what it is doing. I did learn a lot and for the price it is still worth it.

A really good and detailed course on sequence models. This was definitely the most challenging course in the specialization so far in part because of the use of the Trax framework. I really enjoyed reading the source code of Trax and understanding how the ML framework was constructed. This was a very unique part of this course.

Excellent course, I would like to learn a little more to know how to adjust the classification threshold in the Siamese network, tuning of parameters in the LSTM network, and how to solve common error problems in the models performance. This course is a good base to introduce you to the sequence models.

Excellent lessons and labs, as well as the assignments. I would just like for the grading to give partial points if some tests were passed but not all. For example, I got 0/10 even though my function passed 5 tests and failed one test. Anyway, I am very satisfied with the course!

Phenomenal course! There is a lot of material packed into concise lectures as well as the labs and supplemental notebooks. Its evident a lot of care went into this course. I'm already using what I've learned for some personal projects. Highly recommend this course.

Would have been more useful if all the code snippets, labs, assignments were in Tensorflow or Pytorch. I understand that Trax is more easy to use and deploy. But untill companies really start using this library it is of very less benefit to learners.

Didn't like that the labs are in Tensorflow instead of PyTorch, but that is a personal preference In other terms, it is a great course, especially the last week, in which the basics of metric learning are smoothly explained

Overall it was great a course. A little bit weak in theory. I think for practical purposes whatever was sufficient. The detection of Question duplication was a very much cool model. I enjoy it a lot.

This is the third course of NLP Specialization. This was a great course and the instructors was amazing. I really learned and understand everything they thought like LSTM, GRU, Siamese Networks etc.

Awesome course!! Younes explains all the concepts very nicely :) I enjoyed this course a lot and learned many new things, which I am planning to use in my current project. Thanks a lot, Younes

This course is much more difficult than the 2 previous ones in the series. Not because of the way instructor transferring but in the knowledge itself. Totally worth taking this course

Excellent course on sequence models and how to solve problems in industry and academia with them. Beautifully structured assignments and well-explained lectures, quite enjoyable!

I wish the neural networks would be described in greater detail.

Everything else is really nice, Younes explains very well. Assignments are very nicely prepared.

I finished the other courses in this specialization, and I'm really enjoying it. Younes explains very well and the assignments are very nicely prepared!

amazing course. material is very well presented and explained! really loved the data generator part of the code - really drilled in the importance of it!

Interesting course. I like this specialization very much. I don't understand why one instructor introduces the topic and another instructor explains it.

Concise, to the point, and very insightful/educational. Take it in conjunction with the general Deep Learning Specialization, you'll not regret it.