Comencé esta especialización sin conocimientos de deeplearning en absoluto, hoy habiendo finalizado la especialización tengo una basta noción de este mundo tan apasionante. Quiero destacar la facilidad con la que Andrew transmite su conocimiento, es un instructor de otro mundo!. Feliz de haber realizado la especialización y de continuar por este camino. Gracias a Andrew Ng. y a Coursera.

This is an incredibly great course for learning Deep Learning. The course lecture videos and the programming exercises are both so well designed! By learning this course, I have got a comprehensive understanding of Deep Learning framework, as well as the hands-on experience of using deep learning to solve real-world applications. Thank you for providing this wonderful series of courses.

Loved the course, Andrew is a great teacher; very impressive ability to explain and give intuition. I can really see how I can build upon this course to help me in what I am doing at work. I think there is definitely some room to go deeper on some of the topics e.g. don't just teach sequence to sequence but also broader uses of recurrent networks. Maybe a follow-up course? ... please???

First of all I would like to thank all of the people given me opportunity to follow this course. This is the toughest course I followed so far with latest greatest technology stack in 21st century. Over the past few months I gained a lot of knowledge and experience from all of the courses and I hope now I can apply the knowledge of deep learning specialization for my future projects.

This module of the specialization is a bit more complicated than the others; at least to me, I found the concepts more difficult to grab.

Anyway, thank to Andrew and his team for this amazing specialization. The lectures are great, the assignments are fun and have interesting examples. A huge amount of knowledge along all the courses. You can tell there is a lot of work behind it.

THANKS

I was about to give this course a 3-star rating unlike the other courses in the specialization, which I have rated 5 stars. The reason for that was the programming exercises in week 1. They are not interesting and do not impart a lot of learning. Please consider improving those. The reason I still gave 5 stars is because of the amazing programming exercises in weeks 2 & 3. Thank you.

I have completed all the courses of the specialization and learned a lot. My motivation for this was not professional advancement, as I am only a few years away from the end of my professional career, but pure interest. Interest in one of the most exciting topics of our time. Thanks to everyone at Coursera, especially Andrew NG for all the interesting insights into machine learning.

It was really wonderful course. From here i had learn most important algorithms like LSTM and GRU. I had learnt how to deal with sequence model. Hope I will be better perform on different data.I am really really thankful to coursera to provide such legend teacher. Once again thanks for this beautiful course. Now i had clear my goal. I want to be something in the field of ML and Ai

In the continuity of the 4 previous modules, the Sequence Models course is of very high quality, the material is concise but cover a wide range of applications and methods, and is delivered with consistent clarity. The programming assignment gives very good hands challenges. I highly recommend this course to anyone interested in natural language processing or speech recognition.

This is the last course of the Deep Learning journey, and I felt like a learned a lot in it. Sequence Modelling is a different beast compared to non-time series models, but I've mastered it thanks to this course nevertheless. I would recommend this particular course to anyone who has a moderate understanding of deep learning and wants to get into time series analysis and nlp.

A succinct overview of a number of ideas in sequence models. Some of these were covered in an NYU course I took 4 years ago (embeddings, LSTM), others I had heard about but hadn't had a chance to look into (attention). The assignments were set up to be pretty easy, but I think trying to do them from scratch rather than by filling in code would make for a pretty good project.

It is a well designed course (especially for week 1 - week 2) which gave a comprehensive view of the sequence model. However, week 5 material can be better and clearer. To be specific, additional hints can be given in the coding exercise. Video can be better aligned with the material in the coding exercise. Thank you Andrew and all the contributors for this amazing course!

Great introduction to sequence models/RNNs. The real-world examples were very illuminating. Again, as with the previous course in the specialization, I felt some details of how to run/predict NNs using keras were lacking, which could leave a student floundering if they've never used keras before. This is in contrast to some other, much easier, tasks where hints were given.

Out of 5 courses offered I think this was the most exciting one as it combines everything learnt so far and teaches how to combine different NN modeling techniques to achieve desired classification/prediction features . For example, it is pretty much clear how one would go about building an app that would describe a picture to blind people and do that in many languages.

This short 3 weeks courses will make you work a little, exercice take at least twice the time write. You will learn about the famous LSTM, and how to use it on various tasks.

I'm not sure the 'translation' tasks is a good example but there is lot about it. Not a good example, because it is not state of art, and in the 'translation' business there place only for the best.

This is a great course, and a great specialization. The professor explains the concepts across very well, not only in this course but in all courses of the specialization. My only gripe is with the notebook/hub/grading system which especially in this course has acted strange and cost a lot of time. That said I've learnt a lot, and am quite happy with the course content.

Great course overall to learn the basics of sequence models and also get a brief understanding of the state of the art architectures used currently. The programming assignment on trigger word detection gives an insight into the practical machine learning implementation for speech recognition. This course combines both theory and practical advice in a very good fashion.

Excellent course - and specialization! Andrew Ng's special talent is in being able to explain complex and difficult stuff with such clarity that you can actually understand it and follow. I found the exercises in this course tougher than in the previous four, but they were varied, useful, and FUN! Highly recommended to all who what to learn the "deep" in Deep Learning!

Because my research direction is NLP, so I think this course is very good for me. I learn how to implement the Sequence model such as machine translation 、Attention and so on. But the disadvantage is that there is no whole sequence model process. For me, The bigger problem is data processing and model. overall ,This course is good for me, I learned many from this.

It was a great specialization and a great course, thank you so much for giving me the opportunity to learn from you special thanks to Dr. Andrew Ng for his exemplary efforts and for teaching the greatest courses of the machine learning technology, I'm really proud of myself for finishing that specialization and I'm so grateful for all of you. Thank you ,Coursera.

Very clear delivery of material and lots of tips for real world applications. Appreciate the hard work that Andrew and everyone who contributed to the course material and mentors on preparing an amazing specialization. Machine learning is not the most straightforward subject to learn and having such a well structured course goes a long way in getting us started.

The whole specialization is excellent. I highly recommend doing it. The only minor comment that I add is that Andrew should include some links for further reading (along the courses for each topic or theme). I know that anyone can quickly look up for them in the Internet (and they can be outdated) but that would make the specialization even better in my opinion.

This is Course 5 of the Deep Learning Specialization, and the last one. We learn Recurrent Neural Network (RNN) /Sequence Model, which allow translation or trigger word (like "Hey Siri!"). It's a completely different beast than CNN seen in Course 4. Again, nice videos and explanations, and well-designed useful programming assignment (TensorFlow/Keras and numpy)

I Highly recommended this course on Sequence Models. The course is easy to follow as it gradually moves from the basics to more advanced topics, building gradually. Andrew Sir makes the cocepts behind the scenes about LSTM GRU etc very easy to understand. Assignments are great, extremely well designed. Best assignments you will ever get to practise and learn.

The kind of simplicity with which the course is explained and the amount of knowledge gained is worth the hard work of many months! . . I would like to thank the whole Coursera team and Sir Andrew Ng for creating such a wonderful platform and a big shout-out to all the mentors and community who have replied to the most basic queries in the discussion section.