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Learner Reviews & Feedback for Sequence Models by DeepLearning.AI

4.8
stars
26,842 ratings
3,180 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

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!

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.

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2551 - 2575 of 3,170 Reviews for Sequence Models

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 Abid

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 Harry 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 Nguyen H S

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 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.

By Ryan

Jul 15, 2021

I​ think the transformer programming exercise of this fifth course is not as good as the others. The methods we must implement are not clearly explained and the research on these really took me a huge amount of time.

By Prateekraj S

Jul 28, 2020

The exercises are too short and too basic for this course specifically. The task is a great learning experience but there is not much one would struggle with in terms of difficulty as there is too much spoon feeding.

By Ivan

Mar 18, 2019

Great video lectures, but practical assignments are a pain due to awful auto-grading system and programming expirience in Jupyter in general. Most of the time you'll be searching for an error that isn't really there.

By Fabio R

Oct 31, 2020

Excellent course, excellent lecturer. Unfortunately some of the test data (week3/lab/trigger word detection/XY_dev/* CANNOT BE DOWNLOADED ... The programming lab sections are nice - sometime a bit too helped ... ;)

By Jeffrey D

Mar 11, 2020

Programming exercises did show you quite a bit, but got complex enough that most of my time was spent reading and understanding the preamble than doing any programming. That being said it delivered on the promise.

By Salamat B

Sep 24, 2018

Course content is really good! However, I found it quite difficult to truly understand deep learning algorithms. However, it provides good glimpse of of sequence models and intuitions behind various useful models.

By Georges B

Feb 20, 2018

Great course and material, Andrew NG really know who to explain difficult subjects in an intuitive way. However, the course seems that it still needs some work (there are some bugs in the lectures and assignments)

By Mayank A

Jun 30, 2020

The NLP Section of this course is quite difficult to understand(The Notations are quite confusing as well as prior knowledge is required to understand) but other than that RNN, GRU, LTSM are explained clearly.

By Seungjin B

Sep 8, 2018

Week1 lessons are a little complex than the previous classes and there are gaps between ground-up python version and keras version of LSTM model. Keras will need to be taught a bit more in detail to follow up.

By Lester A S D C

Jul 29, 2019

This is by far the hardest course in the specialization. But it was explained well. My only complain is there were errors in the first programming exercise. All in all, I learned a lot in this specialization.

By Guoqin M

Jul 2, 2018

Great content! I really love Andrew's teaching style. (1 star deduction for some programming assignments where I spent time debugging but it turned out that the point deduction was due to the grading system.)

By Divya G

Mar 25, 2019

The programming exercises are a little heavy in this course where we need to load and re-load for them to give correct output even if the code had been correct all throughout. Otherwise, the course is great.

By Mathieu D

Sep 10, 2018

4 stars and not 5 stars because the course is shorter than the others and it feels like an exemple in classical forecasting is lacking (sales, time series...).

Really interesting but may be too focus on NLP.

By Zhaoqing X

Jul 24, 2018

It's an excellent course! I will give it 5 stars if it could offer more interesting and meaningful assignments(Not offend, but it a little too easy and the assignments are not very related to the real work).

By Ayush N G

Sep 23, 2019

The course should contain more explanation about natural language processing like tf-idf,lemmatization,stemming,dialog flow. Although i got a good explanation of working of RNNs,LSTM and machine translation

By Md Z S

Feb 3, 2019

Great course to start off with sequence model. The programming exercises were in depth and deliver a great learning experience. Would love to see more of sequence literature in the course's future versions.

By Michele I

Apr 18, 2018

Again a brilliant course from Andrew NG, but though and dense this time. In order to grasp the meanings videos and lectures need to be revised a few times. Also, get some extra info elsewhere does not hurt.