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Excellent course! This course extensively covers all of the relevant areas of NLP with a strong practical element allowing you to applying Deep Learning for Sequence Models in real-world scenarios.
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So many possibilities will be presented in front of you after this course. The only limit is the boundary of my imagination and creativity, that is how I feel now upon the completion of this course.
By Carlos A L P
•Jan 4, 2021
Good continuation of RNNs covering theory and Python exercises using a few algorithms and uses cases. I would love to see more content and more interesting examples to implement in Python. Still, this is a nice introduction to sequence models
By Semion B
•Aug 29, 2022
Amazing information. My one complaint is that the assignments don't help you understand how to work with TensorFlow. Most of the time I would read the documentation on the functions and follow the syntax. Maybe it simply comes with practice.
By Jeremy O
•Apr 9, 2021
I really liked it, however I don't feel like it really went into some of the more practicle issues with sequence models. I was left feeling like I wouldn't really know what to do in a situation where I had highly variable sequence lengths.
By Paulo M
•Oct 7, 2020
I preferred the first specialization courses. The explanations are not so clear as the explanations in the first courses. I will make the NLP specialization to have a better understanding. Anyway, I recommend the specialization. Very good!
By Óscar G V
•Jan 27, 2019
It is a very good course. Andrew Ng explanations are very clear and easy to understand with a lot of good examples. On the other hand there are some confusions or errors in the backpropagation part of the programming assignment about LSTM.
By Sajal J
•Jul 22, 2020
I am rating this course 4 because It doesn't give any guidance about future career paths and next things to learn. The explanations are very good. I understood complex things like GRU, LSTM, Bidirectional RNN, attention model very well.
By Diego A P B
•Mar 7, 2018
While a great introduction on RNNs, I felt there could be another week of lectures given the complexity of the algorithms being explained. Likewise, the programming exercises felt unpolished in some parts, like in the expected outputs.
By Luiz C
•Feb 11, 2018
Very good. To make it perfect, would have liked it for the Assignments to have less bugs (cf. LSTM backprop), and a longer course with extra weeks to present LSTM in the context of prediction (finance, weather, pattern recognition,...)
By Michael M
•Nov 2, 2018
Great course! only negative is that problems would really hold your hand. I don't think there is any way I would pass a whiteboard test on any of this (then again a course to get me to that level would have to be double this length).
By Joshua H
•Jul 20, 2020
The course covers one of the most influential developments in deep learning in recent times, and does so in a thorough way, introducing majority of the relevant mathematics and methods necessary to build a variety of sequence models.
By Jaiganesh P
•Feb 18, 2019
The course is really good if you want to get a good understanding on the basics of deep learning. It would have been great if the course had more hand's on assignments than fill in the blanks kind of assignments in ipython notebook.
By Rohit K
•Jul 7, 2019
I learnt a lot from this course and the whole specialization. I am grateful to the mentors and instructors. If coursera gives me opportunity I can also be mentor for the specialization to help the newcomers through the assignments.
By Ghassen B
•Oct 17, 2019
During the first week, I think that a deeper explanation of the matrices' dimensions throughout the NNs should be given. Indeed, this would be helpful to understand some concepts.
Apart from that, it was an awesoome course, thanks!
By Stéphane M
•Jun 22, 2018
The course was good except first week. I did not learn as much as I would like from the programming exercises of week 1. It could be nice to have 4 weeks instead of 3 for this course. Taking more time to cover the week 1 material.
By Shrishti K
•Jun 26, 2020
Everything is perfect, the teaching is excellent, the only problem is the jupyter notebook, its sometimes difficult to debug issues and takes a lot of time and is kind of vague as well in terms of application of the lectures.
By M H E
•Feb 20, 2023
Thanks to Andrew Ng and his amazing team, this course challenged my fundamental knowledge of Tensorflow and ML algorithms in the most useful way. However, I expected more applying libraries to design the NLP recent products.
By Abid O
•May 1, 2018
some topics not explained in detail. Not enough examples to understand some models completely. As an example, I didn't fully understand what are the parameters for the models, their shapes, and how they are used in the model
By Yash R
•Jan 23, 2022
Great course! But I find the transformer assignment bit difficult. I think if the implementation would be covered in a 10-15 minutes video it would be a lot more easier to understand. Thank you for the great specialisation!
By Jiachang L
•Jul 16, 2018
Overall it was pretty informational on introducing NLP to me. However, Keras was a little bit frustrating to learn at the beginning. I found out the forum was a very good resource to learn Keras syntax whenever I was stuck.
By Eric C
•Jan 12, 2020
Great course! I do feel like I'm just scratching the surface of the types of applications that I can make. I think the coding segments still hold our hands a little too much, but you can't beat the clarity of the lectures.
By Son N
•Oct 21, 2018
The course lecture is grade but I hope the assignment is better in guiding structure, something the explanation is hard to follow, and the assignment should include the transfer learning instead of using the trained model.
By Sehyun P
•Jul 21, 2023
Until chapter 4 it is straightforward to follow the lecture and the assignment, but RNN(especially NLP, and transformer chapter), it gets too difficult to follow what Andrew said and apply it to the following assignments
By Paolo S
•Jun 8, 2019
This was hard to keep up with, maybe too hard. The assignments' difficulty also was on a different level then the lectures maybe there more time should be put into the lecture videos as it was the case for DNN and RNN.
By Aida E
•Feb 21, 2018
The videos and programming exercises were very interesting and insightful. My only complain is some of notebooks for exercises include errors and it was just a time-wasting task to find the "trick" to pass the grader.
By Anshuman M
•Jul 30, 2018
The content is well captured and Andrew really helps build the required intuitions. But, the assignments are too guided. There is no room to struggle for solutions which often proves to be the main source of learning.