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19,328 Bewertungen
2,099 Bewertungen

Über den Kurs

This course will teach you how to build models for natural language, audio, and other sequence data. Thanks to deep learning, sequence algorithms are working far better than just two years ago, and this is enabling numerous exciting applications in speech recognition, music synthesis, chatbots, machine translation, natural language understanding, and many others. You will: - Understand how to build and train Recurrent Neural Networks (RNNs), and commonly-used variants such as GRUs and LSTMs. - Be able to apply sequence models to natural language problems, including text synthesis. - Be able to apply sequence models to audio applications, including speech recognition and music synthesis. This is the fifth and final course of the Deep Learning Specialization. is also partnering with the NVIDIA Deep Learning Institute (DLI) in Course 5, Sequence Models, to provide a programming assignment on Machine Translation with deep learning. You will have the opportunity to build a deep learning project with cutting-edge, industry-relevant content....



Jul 01, 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.


Mar 14, 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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2026 - 2050 von 2,076 Bewertungen für Sequence Models

von bernd e

Mar 10, 2018

Should be five weeks instead of three. Dive deeper into Details

von Ar-Em J L

Oct 30, 2019

One of the weaker courses in the specialization. Felt rushed.

von Danilo G F R

Feb 06, 2018

Assigments too complicate without a necessary guide and help.

von André T D S

Oct 02, 2018

Bugs in the programming assignments grading kills the flow

von Santosh B

Feb 19, 2019

I felt the last week had too many things packed together

von Shrishty C

Jul 06, 2018

Was little hard to understand at times. But it was good.

von Konpat P

Feb 16, 2018

Not as well done as before. But, still very informative.

von Edoardo B

Nov 15, 2019

Doesn't teach much about keras which is sorely needed

von Rajesh S

Feb 25, 2018

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

von karishma d

Jun 20, 2019

very basic ..would have wanted much advance level .

von Saumya T

Jun 09, 2019

Codes are not explained. Some codes files are given

von Sravan

Apr 19, 2019

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

von Yue

Apr 26, 2019

Esperaba que los ejemplos fueran de otra forma

von Jazz

Oct 11, 2019

Should add some instruction videos of Keras

von Shanger L

Jun 05, 2018

does HW created/reviewed by different ones?

von Parikshit D

May 27, 2018

The assignments are not very satisfactory..

von Xueying L

Jul 22, 2018

Too narrow focusing on applications in NLP

von Ritesh R A

Feb 03, 2020

Course should have have more descriptive

von Liang Y

Feb 10, 2019

Too many errors in the assignments

von stdo

Sep 27, 2019

So many errors need to fix.

von ARUN M

Feb 06, 2019

very tough for beginners

von Wynne E

Mar 14, 2018

Keras is a ball-ache.

von Long Q

Mar 17, 2019

too hard


Jul 26, 2018


von 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 .)