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Avis et commentaires pour l'étudiant pour Sequence Models par deeplearning.ai

4.8
17,182 notes
1,877 avis

À propos du cours

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. deeplearning.ai 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....

Meilleurs avis

JY

Oct 30, 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.

AM

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.

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1 - 25 sur 1,859 Examens pour Sequence Models

par Dylan R

Oct 20, 2018

Tons of editing errors in lectures, and the programming problems rely more on knowledge of Keras (essentially untaught throughout the course) than they do on understanding of lecture material. A disgraceful end to an otherwise solid course sequence.

par Lewis C L

Apr 15, 2019

Full of appalling errors that have been present for over 1 year. No one fixes it. It is clear that since Ng was let go by Stanford and Baidu, he is trying to earn a living with deep learning_ai. This apparently is not working as the small income from Coursera is not sufficient. As a result the prerecorded classes remain on Coursera to accrue some residual income. But, Andrew Ng and the staff are apparently gone.

Sadly, since these classes are no longer based on REAL Stanford classes the quality has gone downhill. I would recommend not taking the deeplearng_ai classes. Stick to classes offered by currently employed professors at established universities--preferably classes that ARE the same as the university classes or, at least, those derived from actual classes.

par Bogdan P

Nov 03, 2018

I really like the deeplearning.ai specialization. And also I like the Sequence Models course. However, I feel that I have learned less during this course comparing to the other ones in the specialization. First, I believe it was an extensive use of Keras. Whereas the framework is great, it would be much better for understanding if all the exercises were in numpy, whereas Keras tween-projects be optional. Doing both numpy and Keras versions would allow to better understand the material and learn through repetition. Second, even though the course is great, I perceived the number of errors/typos was much higher than in other courses. Is that true? For example, the Jazz Improvisation exercise was a nightmare. Overall, thank you for the course. Despite those problems, I would still recommend it.

par Alex R

Jun 15, 2018

Keras is required to pass the assignments but no training provided for it. I can learn it myself of course but then the question is this - what am I paying for?

par Andrés F R

Nov 08, 2018

I want to thank Andrew Ng and his team for the amazing work. You definitely make the world a better place sharing this knowledge, and it is an inspiration.

To the contents: the course covers many uses of sequence models, for many different formats (many-to-one, many-to-many...), the questionnaires are focused but comprehensive and the programming exercises cover a wide range of difficulty levels, from no-brainer-one-liners (most of them) to implementing LSTM backprop by hand (optional). They take away the dirty work from you but make sure you get how you would do it. At the end you get to work with pretty complex setups like the attention model, but you still get the feeling of knowing how it ticks from the very bottom up.

The actual merit is that, even if it feels simple, it actually does work and is a takeaway knowledge that can be directly applied for personal setups. And mr Ng's videos are a charm, you can totally feel the care. Glad to see him back after so many years :)

Cheers

par Nathan P

Feb 20, 2019

I'm blown away by how quickly this series of courses brought me from thinking a neural network was a magic box full of fairy dust, to being able to understand even the (al)most complex of network architectures and what makes them tick at every level at a glance. A lot of time has obviously gone into structuring this course; not an ounce of fat present and the format of developing intuition before diving into the nitty gritty and optional further learning resonates with me on so many levels. Thank you Andrew Ng and the team at deepmind.ai and coursera!

par Jizhou Y

Mar 02, 2019

Professor Andrew is really knowledgeable. I learn a lot from his lecture videos.

par khushal m

Apr 11, 2019

I think it is the best courses designed so far. Gives you exactly the appropriate amount of information needed to understand basics behind sequence models. A must do course for all the students who want to pursue a career in this field.

par Ng K W P

Apr 11, 2019

If not Internet, I would not have been able to study a world-class Deep Learning course at an affordable price. Thanks Andrew and team.

par Abhijeet M

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.

par Ozioma N

Jun 09, 2019

Great module, I am lucky to have used this resources in learning sequence models, I can imagine running LSTM using one of the frameworks without ever implementing it myself, Andrew Ng/Deeplearning.ai is the best!

par Sonia B

Feb 19, 2018

Loved the course - it was very interesting. It is also pretty complex, so will probably go through it again to review the concepts and how the models work. Thank you for this wonderful course series!

par Jason J D

Sep 11, 2019

Wonderful end to this Deep Learning Specialization. The programming assignments cover up a variety of hot topics in the Deep Learning market. The videos are very well made and teach the content in depth. A special thanks to Prof. Andrew for yet another amazing course in this wonderful specialization!

par Ravi K S

May 20, 2019

Could have been more thorough like previous courses

par Johannes J

Jun 27, 2019

Great insights, helpful notebooks, good explanations.

par Beibit

Jun 26, 2019

Little bit math heavy. It was sometimes hard to understand the intuition, e.g. RNN, LSTM, GRU

par Jaime G

Jun 27, 2019

Some coding assignments were too hard to follow what was required.

par Juan F C U

Jul 12, 2019

Many topics are only quickly skimmed over. Serves as an overly brief introduction to RNN.

par Oscarzhao

Apr 02, 2018

some optional exercises are wrong, wasted a lot of time on LSTM backward propagation

par Isaraparb L

Jul 26, 2018

Unfortunately considerably a subpar course compared to the other four in the specialization. Programming assignment is a mess - wrong formulas presented, nowhere near enough Keras's tutorials, etc. Every assignment is passed by browsing the forum looking for help from other people. It is unclear to the point of being annoyed (got someone in the forum cancel his subscription). However, lectures are fine and sequence models cover a wide range of areas/applications, so you can't miss it anyway.

par 宇翔 蔡

Mar 06, 2018

there are a lot of mistakes in programming assignments.

par Kirk P

Jul 01, 2018

The lectures were great. Andrew is a wonderful teacher, but the assignments were beyond miserable. Jupyter notebook is probably the least stable, most infuriating piece of software that I've been forced to interact with. I spent countless hours trapped, not able to perform the most basic of operations, such as saving my work or submitting. I lost work innumerable times. I, like others, eventually resorted to "saving" my work by copying it into a text editor on my system for fear of Jupyter sabotaging me. Even if the system was stable, most of the assignments were worthless as learning experiences. The majority of "programming" boiled down to playing a cryptic game of fill in the blank. Bottom line, I wouldn't recommend this class to anyone in its current state. Especially as a paid service. I really expected better quality.

par Marc B

Jul 12, 2018

This one went a little fast for me, can't say that I'm confident on the shapes of tensors going through RNNs and why

par AlainH

Feb 05, 2018

This course has many inconsistencies and errors in the homework. Seems like a rushed job.

par Kiran M

Feb 16, 2018

This course felt rushed. Especially, the programming assignments, which had many errors and were frustrating at time. It is still worth it since the content is really good -- only if you are willing to go through the frustration during the programming exercises.