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

4.8
estrelas
26,472 classificações
3,121 avaliações

Sobre o curso

In the fifth course of the Deep Learning Specialization, you will become familiar with NLP models and their exciting applications such as speech recognition, music synthesis, chatbots, machine translation, natural language understanding, and more that have become possible with the evolution of sequence algorithms thanks to deep learning. By the end, you will be able to build and train Recurrent Neural Networks 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. DeepLearning.AI is proud to partner with NVIDIA Deep Learning Institute (DLI) to provide a programming assignment on Machine Translation with Deep Learning. Get an opportunity to build a deep learning project with leading-edge techniques using industry-relevant use cases. The Deep Learning Specialization is our 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 gain the knowledge and skills to apply machine learning to your work, level up your technical career, and take the definitive step in the world of AI....

Melhores avaliações

JY
29 de Out de 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.

WK
13 de Mar de 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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3026 — 3050 de 3,094 Avaliações para o Sequence Models

por Jerry Z T

18 de Ago de 2020

The learning embedding part is kindof confusing

por Prashath M

29 de Dez de 2020

Excellent content

poor support from the website

por Abhishek S

15 de Jun de 2020

Great course but has been dumbed down too much

por Yue E

26 de Abr de 2019

Esperaba que los ejemplos fueran de otra forma

por Jazz

10 de Out de 2019

Should add some instruction videos of Keras

por Shanger L

4 de Jun de 2018

does HW created/reviewed by different ones?

por Parikshit D

27 de Mai de 2018

The assignments are not very satisfactory..

por CLAUDIO G T

5 de Abr de 2020

Not so well explained as the other courses

por Xueying L

22 de Jul de 2018

Too narrow focusing on applications in NLP

por Rahul T

9 de Ago de 2020

Programming exercises was very confusing.

por Ritesh R A

2 de Fev de 2020

Course should have have more descriptive

por Liang Y

10 de Fev de 2019

Too many errors in the assignments

por guzhenghong

17 de Nov de 2020

The mathematical part is little.

por julien r

25 de Mai de 2020

second week was hard to follow

por stdo

27 de Set de 2019

So many errors need to fix.

por ARUN M

6 de Fev de 2019

very tough for beginners

por Wynne E

14 de Mar de 2018

Keras is a ball-ache.

por Long Q

17 de Mar de 2019

too hard

por CARLOS G G

26 de Jul de 2018

good

por Debayan C

23 de Ago de 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 .)

por 象道

16 de Set de 2019

i really learned from this course some ideas on recurrent neural net, but the assignments of this course are not completely ready for learners and are full of mistakes which have existed for more than a year. those mistakes in the assignments mislead learners pretty much if they do not study some discussion threads of the forum. this course has the lowest quality among all of Dr. Andrew Ng's. before the updated versions, a learner had better have a look at the assignments discussion forum before starting the assignments.

por Luke J

31 de Mar de 2021

The material really is great, but work needs to be done to improve the assignments, specifically submission and grading. On the last assignment I spent way more time troubleshooting the grader than the content of the assignment. It can be very frustrating to have to do this on a MOOC where no human support is available. It appears, specifically for this assignment based on discussion that this has been a problem for a very long time.

por daniele r

15 de Jul de 2019

The subject is fascinating, the instructor is undoubtly competent, but there is a strong feeling of lower quality with respect to the other 4 courses in the Spec (in particular the first 3). Many things in this course are only hinted to, without many details. Man things are just said but not really explained. Many recording errors as well. Maybe another week could have helped in having a little more depth in the subject

por Amir M

2 de Set de 2018

Although the course lectures are great, as are all the lectures in this specialization, some of the assignments have rough edges that need to be smoothed out. It is particularly frustrating for those trying to work on the optional/ungraded programming assignment sections that have some incorrect comparison values, as much time will be wasted trying to figure out the source of the error.

por David S

19 de Dez de 2020

Excellent lectures, terrible exercise material. E.g. "You're implementing how to train a model! But we've done the actual training for you already! Your exercise is to add numbers A and B! Number A is 4. Number B is 11! Enter A + B in the box below!" Also, someone did a search-and-replace and converted every sentence into an individual bullet point to reduce readability.