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Learner Reviews & Feedback for Sequence Models by DeepLearning.AI

4.8
stars
29,853 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

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.

JY

Oct 29, 2018

The lectures covers lots of SOTA deep learning algorithms and the lectures are well-designed and easy to understand. The programming assignment is really good to enhance the understanding of lectures.

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2976 - 3000 of 3,621 Reviews for Sequence Models

By Bhargav A

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Dec 25, 2018

great course, lots of implementation details that are important were glossed over, while other areas had too much hw hand-holding + strict requirements on what the code needed to look like.

By Elias R

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Jan 26, 2024

Its a very good overview. I feel the last course somehow took a big jump and became a bit hard, because one module is not enough. It makes sense, that there is an extra NLP specialisation.

By Austin B

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Feb 20, 2018

Very glad I took this course! A little rough around the edges as far as video / assignment quality, but seeing that this is the very first run of this course, I know it will only improve.

By Zachary P

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Feb 11, 2020

The material was great. Some of the programming assignments ramped up in difficulty or lack of perfect execution. However, I still gained extremely valuable information from this course.

By akyang

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Oct 1, 2019

The lecture for Sequence model was good motivation to get interesting about text and audio processing. All of lectures were very fundamental and intuitive. Thank you very much. Prof. Ng.

By Tamir B

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Feb 26, 2019

Very good and fun course in the sequence. However, it would be very nice if there were some examples of using RNN for things such as self driving etc, outside the realm of speech and NLP

By Tamilarasu S

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Feb 16, 2018

The course videos are very good. However the optional parts of assignments have lots of issues and errors. Please update the assignment to reduce the time wasted unnecessarily debugging.

By Pierre-Henri S

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Jun 14, 2019

Very interesting exercice and assignments from which a lot is to learn. Content quite complicated which will require from me to come back for review and deepen some points. Thank you !

By Henrique M

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Aug 28, 2018

It was necessary to study extensively the Keras framework to fulfill the code tasks. I suggest an extra module with small simple RNN modeling exercises to better adapt the framework.

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 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