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Learner Reviews & Feedback for Sequence Models by DeepLearning.AI

4.8
stars
26,862 ratings
3,186 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

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.

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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3101 - 3125 of 3,175 Reviews for Sequence Models

By Rajesh R

Feb 25, 2018

GRUs are poorly explained. Unable to get past Week 1.

By Kenzi L

Jul 19, 2020

a bit outdated due to lstm being not that s-o-a now

By karishma d

Jun 20, 2019

very basic ..would have wanted much advance level .

By Saumya T

Jun 9, 2019

Codes are not explained. Some codes files are given

By Sravan

Apr 19, 2019

Works as a primer. Assignments aren't that great.

By Jerry Z T

Aug 18, 2020

The learning embedding part is kindof confusing

By Manorathna G P K

Dec 29, 2020

Excellent content

poor support from the website

By Sara S A

Jun 15, 2020

Great course but has been dumbed down too much

By Yue E

Apr 26, 2019

Esperaba que los ejemplos fueran de otra forma

By Jazz

Oct 10, 2019

Should add some instruction videos of Keras

By Shanger L

Jun 4, 2018

does HW created/reviewed by different ones?

By Parikshit D

May 27, 2018

The assignments are not very satisfactory..

By CLAUDIO G T

Apr 5, 2020

Not so well explained as the other courses

By Xueying L

Jul 22, 2018

Too narrow focusing on applications in NLP

By Rahul T

Aug 9, 2020

Programming exercises was very confusing.

By Ritesh R A

Feb 2, 2020

Course should have have more descriptive

By Liang Y

Feb 10, 2019

Too many errors in the assignments

By guzhenghong

Nov 17, 2020

The mathematical part is little.

By Julien R

May 25, 2020

second week was hard to follow

By stdo

Sep 27, 2019

So many errors need to fix.

By ARUN M

Feb 6, 2019

very tough for beginners

By Wynne E

Mar 14, 2018

Keras is a ball-ache.

By Long Q

Mar 17, 2019

too hard

By CARLOS G G

Jul 26, 2018

good

By Debayan C

Aug 23, 2019

As a course i think this was way too fast and also way too assumptive. I wish the instructions were a bit slow and we broke down more into designing bilstms and how they work and more simple programming excercises. As a whole i think 1 full week of material is missing from this course which would concentrate on the basic RNN building for GRUs and LSTMs and then move on to applications. I usually do not review these courses and they are pretty standard but this course left me wanting and i will consult youtube and free repos to learn about it better. I did not gain confidence on my understanding. Barely scraped through the assignments after group study and consulting people who know this stuff (which defeats the purpose of this course i believe. It is to enable me with concrete understanding and ability to build these models . It shouldn't lead me to consult others and clear out doubts .)