WK
Mar 13, 2018
I was really happy because I could learn deep learning from Andrew Ng.
The lectures were fantastic and amazing.
I was able to catch really important concepts of sequence models.
Thanks a lot!
MK
Mar 13, 2024
Cant express how thankful I am to Andrew Ng, literally thought me from start to finish when my school didnt touch about it, learn a lot and decided to use my knowledge and apply to real world projects
By Dmitry T
•May 3, 2018
I liked that this course was a bit harder than others in the specialization (well partly because It felt like notebooks were made in a bit of hurry here) but it was a good thing for me, since I had to think more on the programming excercises, read Keras documentation, derive backprop equations - and I believe such engagement with the topic really allows to understand and remember it better.
By Mary A B
•Mar 18, 2018
It's been so rewarding to apply what I've learned in the previous courses of the Deep Learning specialization to time-based problems. I feel I have a better understanding of how some of the "magic" technology like virtual assistants and speech recognition work. While the material in the first four parts was also very useful, the specialization would have felt incomplete without this course.
By Honza Z
•Jan 21, 2022
Where shall I start...? This module was by far the hardest I made, but I'm really glad I was able to finish it somehow (Searching of my own typos was quite challenging task and I thought my head explodes). Anyway this set of courses is great and I will continue further in my path exploring the world of AI. Thank you guys for the effort you spent to share your knowledge with us. Great job!
By Leandro O B
•Jun 4, 2019
Another outstanding course about Deep Learning.
It teaches Recurrent Neural Networks from the basics up to industry applications such as Speech Recognition and Natural Language Processing. The programming assignments are extremely useful to build strong understanding of the algorithms, which we code "from scratch" with NumPy before using higher level frameworks such as TensorFlow and Keras.
By James P
•Aug 6, 2022
The course assignments were very interesing and engaging - clearly a lot of time has been invested in them. The quizzes were not easy but also not too difficult. The combined quizzes/assignnments helped reinforce the lectures. As always, the lectures were great. Perhaps one improvement would be to allocate another week for the transformers as this material was not as well explored.
By Abe E
•Mar 9, 2020
It's a great class, and Andrew Ng is a great instructor. I wish the exercises were a bit harder. Since the course is aimed at all and I am coming from a graduate degree in the sciences, I realize it's hard to cater to all educational backgrounds. I would have liked to see optional/honors exercises to get us more involved. Other than that, I loved the class. Thanks so much for teaching it.
By Patricio G
•Oct 15, 2021
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.
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 Sampath T
•Dec 16, 2021
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.
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 Stephan G
•Oct 27, 2022
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.
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 M 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.