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Learner Reviews & Feedback for Sequence Models by DeepLearning.AI

4.8
stars
30,203 ratings

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

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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.

GS

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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.

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3026 - 3050 of 3,671 Reviews for Sequence Models

By Anthony T

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Feb 14, 2018

Overall, I really like this module. One possible improvement might be providing more information for backpropagation. Maybe as an optional video or just reading materials. Thank you.

By Bruno s

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Aug 24, 2019

nice course even few chapters could be more detailled technically speaking. However the assignements are very nice and helps to complete the understanding. Many thanks for such work

By DIVYA L K

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Sep 6, 2020

Thank you Andrew Ng for making me comfortable with the deep learning topics on Sequential data...Assessments were interesting ..can be made to enable us better play with the models

By Karan S

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Oct 11, 2019

Week 2 was wonderful to learn and understand. I wish to explore more on LSTM and Attention based models. Video lectures were not enough for me. Still I am happy for what I learnt.

By yuankun x

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Mar 19, 2019

Overall it is a good course. Much need to improve on the feedback of grading of which output is not really helping. Referring to global variables in assignments are really tricky.

By srinivasan v

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Feb 28, 2018

Overall a very good course , i wish the model construction ( i.e. the rationale in stacking up the layers) is covered in bit more detail, otherwise an excellent course, no doubt.

By Rahul S

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May 27, 2018

The assignments can be made a little difficult. Can Include assignments of Image captioning, that would have been great. Overall a great course. Sir Andrew Ng, superb teaching!!

By george v

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Apr 1, 2018

great course as always by andrew. would give it a 5/5 but had some sloppy mistakes regarding the formulas. overal impression : exceptional and highly recommended. thanks andrew!

By Masood J K

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Jul 8, 2020

Compared to the previous courses, this one was a little hard for me. Because Dr. Andrew tried to squeezed a bunch of information in this course. It's a wonderful course though.

By Iain C

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Oct 3, 2019

Some of the assignments are very difficult to pass. I think I understand the concepts but the instructions for the assignments could be a lot clearer and provide more guidance.

By kl

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Aug 3, 2022

The course is great. The assignment sessions are a little confusing. It would be good to show the complete codes for the test cases so that test errors can be easier to debug.

By Apra G

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Apr 12, 2021

I did not feel like I got a super clear understanding on how to use various library functions in keras, I did gain a really good understanding of the underlying models though!

By Marcilio M

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Sep 17, 2024

Great course overall with lots of technical details. Week 4 content on transformers is high-level and makes it difficult and time-consuming to complete the hands-on exercise.

By Gregory S

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May 26, 2020

Excellent content, although the exercises - at this stage of specialization - should focus more on NN architecture, than on pure computational and matrix slicing tasks, imho.

By Kaan A

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Aug 12, 2019

Even though it has some flaws in audio clips and homeworks, programming assignments are fun to do. Great real world applications on this whole specialization is just perfect!

By Lap-hang H

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Sep 8, 2018

The content was quite good as with previous courses in this specialization. Just dropping a star because week 1 material wasn't as clear to follow as the rest of the content.

By JanessaTech2022 Z

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Nov 28, 2019

Compared to the first two sections, I don't think this section is better than those. Anyway, I learnt some concepts about sequence models which I need to dive into in future

By Mikhail K

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Feb 11, 2022

A great course on NLP including Transformers. One star down for quite a brief introduction to transformers (I understand that time passes but you better update the course)

By Tang Y

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Apr 10, 2019

The videos are of high quality as always, while the programming exercises had some error in it. Compare with the previous few courses this one seems not polished so well.

By Steven W

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Jan 18, 2021

I learned a lot, but it really felt like there could have been a whole other week's worth of material, especially talking about newer innovations like transformers, etc.

By Jonathan H

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Dec 31, 2020

This course and assignments helped me understand concepts in NLP. However, it is a little less comprehensive compared to the previous courses in the deep learning series

By David J

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Feb 18, 2018

Thank you Deep learning team for putting together this course. The course has really helped me understand the various possibilities with the knowledge of deep learning.

By Bhavul G

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Dec 31, 2018

The first week was a bit too tough compared to the second and third. So, I felt it was a bit hurried. It could have been distributed into two separate weeks, perhaps.

By Cristhian P

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Jun 28, 2018

This course was very useful. I would make the programming assignments for the first session a bit clear. Other than that, everything was easy to understand and clear.

By Michael L

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Mar 16, 2018

Good, but not as in depth as the other lecture series I found. It is faster paced and skips over much more of the detail at which they go into in the earlier modules.