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Comentários e feedback de alunos de Sequence Models da instituição deeplearning.ai

4.8
estrelas
27,119 classificações
3,227 avaliações

Sobre o curso

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....

Melhores avaliações

AM
30 de Jun de 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.

JS
12 de Jul de 2020

brilliant course, great quality instruction from Andrew Ng. The only faults are that some of the labs have not been supervised properly being a but buggy and a couple of later lectures were very dry.

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2676 — 2700 de 3,223 Avaliações para o Sequence Models

por Amir A

31 de Ago de 2019

It was really helpful, every topics explained very well. However, in my standpoint of view, It did not cover some part in sequence learning, like graphical models.

por Jürgen R

4 de Abr de 2018

Really nice course. Very informative. Unfortunately some programming exercises were a little buggy (the grader especially)...only a total reset of notebook helped!

por dann p

22 de Mai de 2018

this course provide an adequate and what you want to know about recurrent neural network but it does require lots of programming skills to accomplish this course.

por Tom S

26 de Abr de 2018

Good course, but I needed more time than expected, especially for the exercises. For me, that was the most demanding course out of the 5 from that specialization.

por Timothy A

15 de Mai de 2020

A lot of cool material covered from RNNs to LSTMs to Sequence Modeling. But it is a lot to grasp and a lot to understand. Overall, rigor and course is decent.

por Yogeshwar D

29 de Abr de 2020

programming assignments are not teaching us to code independently because of the helpers functions given in utils file. Feels like copy pasting the assignments

por SIRAM N N D S K

6 de Jun de 2020

It is a really awesome course for those who want to get started with deep learning methods in NLP.

Got a very clear insight about GRU,LSTM,RNN,Word Embeddings.

por Rohan S

17 de Dez de 2019

The course is really good, one star less because it requires keras understanding to complete assignments properly. Including a basic intro of keras will help

por Nitin S

11 de Jul de 2020

The time allocated to some of the assigments should be increased. The estimated time in many cases seems to assume that one is aware of Keras and Tensorflow

por Cazaubieilh G

18 de Mar de 2020

To the point ; sometimes it would be nice to explain the research papers more in depth, and link other courses to have more formal mathematical explanations

por ignacio v

18 de Out de 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

por Péter D

8 de Fev de 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.

por Matheus B

3 de Fev de 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.

por Дубровицкий А А

24 de Jul de 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.

por Markus B

5 de Dez de 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.

por Andreea A

31 de Mar de 2019

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

por shengtian z

22 de Mar de 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

por Mahendra S S

21 de Jul de 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.

por SHAHAPURKAR S M

16 de Mai de 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

por Alex M

15 de Fev de 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.

por minsq n

19 de Ago de 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 :)

por Maxim V

5 de Out de 2019

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

por Harshit S

25 de Mai de 2019

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

por Jun W

16 de Mai de 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.

por Octav I

23 de Dez de 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.