Chevron Left
Вернуться к Sequence Models

Отзывы учащихся о курсе Sequence Models от партнера

Оценки: 25,478
Рецензии: 2,998

О курсе

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....

Лучшие рецензии

29 окт. 2018 г.

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.

30 июня 2019 г.

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.

Фильтр по:

2901–2925 из 2,970 отзывов о курсе Sequence Models

автор: Shrishty C

6 июля 2018 г.

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

автор: Konpat P

16 февр. 2018 г.

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

автор: Edoardo B

14 нояб. 2019 г.

Doesn't teach much about keras which is sorely needed

автор: Rajesh R

25 февр. 2018 г.

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

автор: Kenzi L

19 июля 2020 г.

a bit outdated due to lstm being not that s-o-a now

автор: karishma d

20 июня 2019 г.

very basic ..would have wanted much advance level .

автор: Saumya T

9 июня 2019 г.

Codes are not explained. Some codes files are given

автор: Sravan

19 апр. 2019 г.

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

автор: Jerry Z T

18 авг. 2020 г.

The learning embedding part is kindof confusing

автор: Abhishek S

15 июня 2020 г.

Great course but has been dumbed down too much

автор: Yue

26 апр. 2019 г.

Esperaba que los ejemplos fueran de otra forma

автор: Jazz

10 окт. 2019 г.

Should add some instruction videos of Keras

автор: Shanger L

4 июня 2018 г.

does HW created/reviewed by different ones?

автор: Parikshit D

27 мая 2018 г.

The assignments are not very satisfactory..

автор: CLAUDIO G T

5 апр. 2020 г.

Not so well explained as the other courses

автор: Xueying L

22 июля 2018 г.

Too narrow focusing on applications in NLP

автор: Rahul T

9 авг. 2020 г.

Programming exercises was very confusing.

автор: Ritesh R A

2 февр. 2020 г.

Course should have have more descriptive

автор: Liang Y

10 февр. 2019 г.

Too many errors in the assignments

автор: guzhenghong

17 нояб. 2020 г.

The mathematical part is little.

автор: julien r

25 мая 2020 г.

second week was hard to follow

автор: stdo

27 сент. 2019 г.

So many errors need to fix.

автор: ARUN M

6 февр. 2019 г.

very tough for beginners

автор: Wynne E

14 мар. 2018 г.

Keras is a ball-ache.

автор: Long Q

17 мар. 2019 г.

too hard