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Learner Reviews & Feedback for Sequence Models by DeepLearning.AI

4.8
stars
27,363 ratings
3,268 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

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.

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!

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2726 - 2750 of 3,268 Reviews for Sequence Models

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.

By Markus B

Dec 5, 2018

Great course. The only tiny flaw is that the introduction to Tensorflow and Keras was a bit shallow so that I struggled a bit with programming these parts.

By Andreea A

Mar 31, 2019

Instructive course with useful concepts. However, there were many more mistakes in the notebooks compared to the previous 4 courses in the specialization.

By shengtian z

Mar 22, 2018

Awesome introduction, but feels like Andrew is a little bit rushing since it is the last course in the series, I dont feel it is as clear as other courses

By Mahendra S S

Jul 21, 2020

The CNN course was better in this series of courses. This course is also good, but more content could be provided. Still the best small course out there.

By SHAHAPURKAR S M

May 16, 2020

Faced issues regarding assignment submissions. Otherwise, the course is perfect. Would upgrade my review to 5 stars if this issue seems to be fixed later

By Alex M

Feb 15, 2020

Es buen, algo extenso, pero suficiente para avanzar. Algo importante es actualizar los cursos con los nuevos algoritmos, al menos uno, por ejemplo BERT.

By minsq n

Aug 19, 2019

This course is quite challenging, but at least the concepts were well explained. Wished that Andrew and his team could conduct a crash course on Keras :)

By Maxim V

Oct 5, 2019

A great intro to RNN, LSTM, GRU, Activation. Programming assignments are rather messy though (unlike those in the other courses of this specialisation).

By Harshit S

May 25, 2019

Great course, I like the practical application and assignments discussed in this course , wish latest research papers were also discussed in the course,

By Jun W

May 16, 2019

This course introduces mainly about RNN, GRU and LSTM. Great assignments. 1 score off for the in-correction in assignments. 4.5 scores from me actually.

By Octav I

Dec 23, 2018

Great lectures, really well explained, assignments could request more from the trainee to devise the logic instead of having it already defined for him.

By Marcela H B

Jun 28, 2021

Good course, however I would like to have more Transformers application in the last part as well as some information regarding the fine tuning of them.

By Thierry L

Jun 30, 2020

Thank you very much for all the work you have done. I have learned so many things... I will try to use this stuff in the coming months. Yours, Thierry

By Tiago C G M

Mar 3, 2019

The course is really good, I would recommend it to anyone who wants to learn the subject, but it lacks support from the staff in the discussion forums.

By Tomasz D

Oct 3, 2020

Very good course. Some editing issues in the lectures and small issues with the programming exercises (outdated Keras instructions and documentation).

By Nicola P

Feb 14, 2018

The lectures are excellent. The assignments are an extremely valid trace of significant deep learning application, while they lack a bit of challenge.

By Alon M

Oct 13, 2018

As always, this course is great. however, for some reason this course is much more difficult then the others, and i feel as if it is packed too much.

By Michael S

Jul 12, 2018

Really good course, like the others. A bit too black box in some of the programming exercises, so I expect to struggle when developing my own models.

By Yifan E X

Apr 10, 2018

The videos are really informative and well structured. However, the exams felt like Keras tests. A detailed Keras tutorial would have been helpful.

By Takeo S

Mar 28, 2019

It was great course,

I wish we have more speech recognition contents

Hope, you add new course a bit focus on audio/speech recognition etc

Thank you!

By Ara B

Dec 31, 2019

too much content and not much chance to exercise. I will suggest for more frequently and smaller programming assignments through out the course!