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Learner Reviews & Feedback for Sequence Models by DeepLearning.AI

26,419 ratings
3,114 reviews

About the Course

In the fifth course of the Deep Learning Specialization, you will become familiar with NLP models and their exciting applications such as speech recognition, music synthesis, chatbots, machine translation, natural language understanding, and more that have become possible with the evolution of sequence algorithms thanks to deep learning. By the end, you will be able to build and train Recurrent Neural Networks 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. DeepLearning.AI is proud to partner with NVIDIA Deep Learning Institute (DLI) to provide a programming assignment on Machine Translation with Deep Learning. Get an opportunity to build a deep learning project with leading-edge techniques using industry-relevant use cases. The Deep Learning Specialization is our 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 gain the knowledge and skills to apply machine learning to your work, level up your technical career, and take the definitive step in the world of AI....

Top reviews

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!

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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2551 - 2575 of 3,089 Reviews for Sequence Models

By Juan Z

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 Tang Y

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

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

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

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

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

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 Mike

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.

By joris b

Feb 15, 2018

If the programming exercises weren't plagued by some bugs, I would have given 5 star. It's a very complex subject matter, but Andrew takes you through it by the hand.

By Robert L

Aug 28, 2020

I feel week 2 and week 3 materials were covered a bit too quick. Would appreciate more explanation of the implementation details of beam search and activation model.

By Amir A

Aug 31, 2019

It was really helpful, every topics explained very well. However, in my standpoint of view, It did not cover some part in sequence learning, like graphical models.

By Jürgen R

Apr 4, 2018

Really nice course. Very informative. Unfortunately some programming exercises were a little buggy (the grader especially)...only a total reset of notebook helped!

By dang

May 22, 2018

this course provide an adequate and what you want to know about recurrent neural network but it does require lots of programming skills to accomplish this course.

By Tom S

Apr 26, 2018

Good course, but I needed more time than expected, especially for the exercises. For me, that was the most demanding course out of the 5 from that specialization.

By Tim A

May 15, 2020

A lot of cool material covered from RNNs to LSTMs to Sequence Modeling. But it is a lot to grasp and a lot to understand. Overall, rigor and course is decent.

By Aravind R K

Dec 13, 2020

Great way to finish off the DL specialization. Had a blast learning about time sequences and attention models. It was extremely fun to work on the assignments.

By Yogeshwar D

Apr 29, 2020

programming assignments are not teaching us to code independently because of the helpers functions given in utils file. Feels like copy pasting the assignments


Jun 6, 2020

It is a really awesome course for those who want to get started with deep learning methods in NLP.

Got a very clear insight about GRU,LSTM,RNN,Word Embeddings.

By Rohan S

Dec 17, 2019

The course is really good, one star less because it requires keras understanding to complete assignments properly. Including a basic intro of keras will help

By Nitin S

Jul 11, 2020

The time allocated to some of the assigments should be increased. The estimated time in many cases seems to assume that one is aware of Keras and Tensorflow

By Cazaubieilh G

Mar 18, 2020

To the point ; sometimes it would be nice to explain the research papers more in depth, and link other courses to have more formal mathematical explanations

By ignacio v

Oct 18, 2018

Give us one more week to learn RNN for time series in economics, finance, etc!

Programming Exercises need more hints and more training in simple Keras models

By Péter D

Feb 8, 2018

Well-made course, but unfortunately there are tons of mistakes in the programming assignments - in the comments, formulas, even in the prepared code pieces.

By Matheus B

Feb 3, 2018

The best course in the Deep Learning Specialization. Really good and well explained. There are some problems and mistakes in the problem assignments though.

By Дубровицкий А А

Jul 24, 2019

Somes basics, tiny bit of theory, a bit of keras and insights for practical tasks. Some strage errors in notebook exercises makes it 2x time longer though.