Chevron Left
Zurück zu Sequenzmodelle

Bewertung und Feedback des Lernenden für Sequenzmodelle von deeplearning.ai

4.8
Sterne
28,117 Bewertungen

Über den Kurs

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-Bewertungen

AM

30. Juni 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.

JY

29. Okt. 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.

Filtern nach:

2976 - 3000 von 3,372 Bewertungen für Sequenzmodelle

von Filip V

25. Feb. 2018

Provides good exposure to sequence models for NLP and speech processing.

von Xirui Z

7. Apr. 2021

Instructions for labs are not clear enough, especially the layers part.

von Mandeep S G

25. Jan. 2020

Great exercises but videos were slightly rushed. Overall a good course.

von Vinod C

29. Apr. 2019

Good course. Feel a little bit rushed. Difficult to retain the concepts

von Chen L

14. März 2018

The content is great, but the programming exercises are full of errors.

von Xiao

8. März 2018

Some techniques for keras need to be clarified. Generally a good course

von Jon M

7. Juli 2021

I liked this particular set of lectures, too, now on to something new.

von Vamvakaris M

8. Sep. 2019

It required coding on keras and tensorflow not appropriate introduced.

von Rafael B d S

6. Aug. 2019

The Course is great! But the programming assignments has too many bugs

von Pete H

12. Dez. 2018

it's very difficult to submit last programming exercise "trigger word"

von Ishan S

27. Juni 2020

More clarification on what we are doing in the programming exercises

von Emanuel G

13. Dez. 2018

Great introduction to LSTMs, RNNs, GRUs, NLP and speech recognition.

von Nilesh R

20. März 2018

Great content but I felt it was bit rushed and squeezed in 3 weeks .

von Alex M

14. März 2018

The quality was a bit down but still very worthwhile and interesting

von Vivek K

20. Juli 2018

Great practical experience. Would have preferred a bit more theory.

von Fady B

1. Juni 2018

it covered a lot of interesting topics but it was a bit high level.

von Alireza S

18. Juni 2020

great course to understand intuition of sequence modeling for NLP.

von guolianghu

5. Apr. 2020

课程虽然很短,只有三周的课程,但难度明显比之前四门课程要大,编程练习一共有7个,第一周的三个是最难的。但仍然是最优秀的深度学习课程。

von Bobby A

2. Juli 2019

Well explained, I feel like it could go a bit more in depth though

von Martin T

13. Feb. 2018

Muy buen curso, resulta sumamente estimulante el ejemplo de woebot

von Vikas C

20. Juni 2019

The good course as the theoretical basis for RNN and other models

von Shilpa S

18. März 2019

Attention Models is not that clear. Everything else is excellent.

von Andres R

2. Apr. 2018

Excellent lectures. Some programming exercises need more clarity.

von Armand L

28. Apr. 2019

Very hard, but not your fault, very good course ! Thank you !!!!

von Julio T T

28. Sep. 2020

Exercises have less quality than the ones in previous courses.