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Learner Reviews & Feedback for Sequence Models by DeepLearning.AI

4.8
stars
26,828 ratings
3,177 reviews

About the Course

In the fifth course of the Deep Learning Specialization, you will become familiar with sequence models and their exciting applications such as speech recognition, music synthesis, chatbots, machine translation, natural language processing (NLP), and more. By the end, you will be able to build and train Recurrent Neural Networks (RNNs) and commonly-used variants such as GRUs and LSTMs; apply RNNs to Character-level Language Modeling; gain experience with natural language processing and Word Embeddings; and use HuggingFace tokenizers and transformer models to solve different NLP tasks such as NER and Question Answering. The Deep Learning Specialization is a foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. It provides a pathway for you to take the definitive step in the world of AI by helping you gain the knowledge and skills to level up your career....

Top reviews

AM
Jun 30, 2019

The course is very good and has taught me the all the important concepts required to build a sequence model. The assignments are also very neatly and precisely designed for the real world application.

WK
Mar 13, 2018

I was really happy because I could learn deep learning from Andrew Ng.\n\nThe lectures were fantastic and amazing.\n\nI was able to catch really important concepts of sequence models.\n\nThanks a lot!

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151 - 175 of 3,165 Reviews for Sequence Models

By Congyuan Y

May 30, 2020

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.

By Simon R

May 13, 2018

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???

By Fabrice L

Jul 17, 2018

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

By Apoorv V

Jan 3, 2020

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.

By Aman D

Mar 3, 2021

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

By JC Q

Feb 10, 2018

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.

By Mashrur M

Jun 30, 2019

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.

By Peter V

Sep 12, 2018

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.

By C L

Jul 14, 2021

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!

By Guy M

Sep 5, 2018

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.

By Alexander G

Feb 25, 2019

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.

By Kévin S

Jul 31, 2018

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.

By Yogeshwar S

Apr 1, 2018

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.

By sujith

Nov 13, 2018

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.

By Meynardo J

Feb 6, 2018

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!

By 向金芳

Jul 3, 2018

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.

By Ahmed R

Apr 14, 2020

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.

By Matías P B O

Sep 10, 2018

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.

By José D

Nov 6, 2019

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)

By OMAL P B

Apr 10, 2020

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.

By Hardik A

Mar 4, 2019

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.

By Bing H

Jul 27, 2019

Home work assignment notebook has a quick time out issue. It's quite annoying since most of the assignment has lots reading material to fully understand the topic or method. Often the notebook just time out and has to be restarted before move to the next section. Hopefully, it can be fixed or improved.

Overall a very good course to learn about sequence model.

By Jiandong S

Mar 9, 2019

It took me a longer time to finish the course due to busy schedule. But I found it totally worth the struggle to work on the course material. Sequence modeling and processing is an new area to me. The course taught me some basic concepts and gave me a chance to lay hands on through programming exercises. I feel a lot like the topic particularly NLP. Thanks!

By Quentin G

Aug 14, 2018

Très largement plus difficile que tout ce qu'il y a eu auparavant. Un véritable apprentissage et un plaisir surtout sur le Trigger Word Detection qui était très intéressant.

Totally more difficult than anything before. I've acquired true knowledge that I'm very proud of. It was a pleasure, especially for the Trigger Word Detection which was very interesting.

By Lucas O S

Feb 17, 2018

Exercises too basic. Better to do something simpler from scratch, them fill in the blanks on statements like "define a to be a boolean variable initialized to True", and run a bunch of other cells with imported code that hides the actual complexity. These kind of exercises does not add anything to the student. Content of Andrew's lessons is great, however.