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Kursteilnehmer-Bewertung und -Feedback für Sequence Models von deeplearning.ai

4.8
16,683 Bewertungen
1,824 Bewertungen

Über den Kurs

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....

Top-Bewertungen

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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1726 - 1750 von 1,803 Bewertungen für Sequence Models

von Jie Y

Mar 31, 2018

The class covered too less on the Sequence models such as LSTM and GRU. It has too much domain knowledge related videos. Also, it does not have any video related to Time Series.

von Kaupo V

May 07, 2018

The Keras programming exercises are quite weak. Please re-think how to teach them more systematically. Currently it is quite a lot of hit and miss.

von Hans E

Mar 03, 2018

Great lectures, great teacher!

I would have given 5 stars but for the problems in the exercises / grader. Some problems that are know for weeks or even months are not resolved. This causes many wasted hours for many hundreds of students. Please solve this and make it a 5 star course.

Many thanks to Andrew Ng and the mentors!

von Franck B

Feb 17, 2018

Really big struggle with dinos, versions of workbooks, and sometimes no logical way to explain why grader does not validate a working notebook. Pain, frustration, taking away time from proper learning.

On the course itself, some exercices felt like toying (e.g. very simple function to check if a time_segment already exists) in the middle of a keras deep learning model, where learning debugging, setting up smaller ones would have helped me learn more I think.

Still not sure I am at ease with creating models, we experimented various ways over the specialisation, and the selection of model architecture or even tuning after 1st running version is still mostly guess work to me. Will need to digest and keep learning

von Max W

Sep 07, 2018

The course is great but the tasks in Keras are too complex without background knowledge. Therefore, a reasonable introduction in Keras would be desirable.

von Mason C

Sep 12, 2018

Had to rate this lower due to problem with the final assignment. Submission and saving situation was a nightmare, I had to redo my work several times. Please fix this, it's a real downer at the end of the course. Otherwise, content stellar as always.

von Yao G

Sep 12, 2018

The assignments should be improved. More prep on Keras will help improve the efficiency of learning.

von Ashvin L

Oct 22, 2018

The course content is pretty good for breadth. However, it falls short in going into depth. Assignments need to be more open-ended and probably a bit more involved. It appears that we are cutting and pasting code that is already written in comments.

von Noam S

Oct 27, 2018

The lectures were not as good as the previous andrew ng. courses, and the exercises were quite bad in all honesty.

I do appreciate what I have learned, as the lectures WERE clear enough.

von Piotr D

Nov 17, 2018

The course does not explain how to use Keras (it's assumed you've finished the previous course). What's more a lot of code parts is implemented in some difficult way (for loops instead of Python's builtins and idioms like any or list comprehensions). I'd love to see more materials on speech recognition.

von Joshua P J

Aug 01, 2018

The material provides a strong overview of sample problems for which sequence models work well. However, the class doesn't give users the conceptual mastery needed to apply sequence models to new or related problems. The issue is that the motivation and concepts underlying new architectures aren't well-explained (they're often an afterthought at the end of a lecture). This approach to teaching feels backwards.

Specific issues: Week 2 & 3 homework treats lecture material as mostly black boxes so they aren't particularly illustrative. The week 3 Attention Model lectures make no sense, are taught in reverse order, and feel unfocused (with apologies, I know there's a bad pun there; it's not intentional). In Week 3, I ended up skipping to the homework because I found lecture exasperating; to my surprise, the Markdown comment boxes in the Python notebooks explained the material better than lecture did.

von José A M

Aug 05, 2018

Too many stability issues on the platform to get the notebook up and running.

Few bugs and errors on lectures and exercises, if they are found by the community you should update the material even if it involves recording a video again. Too much time spent on the notebooks figuring out "side" stuff that is not what I am here to learn.

While on the course for CNN it covered the state of the art of the field, in LSTM I think there is much more that could have been explained.

I have missed examples on other type of problems like forecasting time series, events and other more business like applications.

Still I learnt a lot and would do it again.

von Michael K

Aug 06, 2018

Assignments are very buggy and instructions misleading or incomplete. However the core material is excellent

von Xueying L

Jul 22, 2018

Too narrow focusing on applications in NLP

von André T D S

Oct 02, 2018

Bugs in the programming assignments grading kills the flow

von Hang Y

Aug 24, 2018

Compared with previous courses, this one seems to be rushed. The focus on applications seems to be much higher than the theoretic side.

von Arjan G

Mar 03, 2018

Nice to learn how RNN's work. But too rough around the edges for a 5-star score.

Good points:

I learned RNNs, language models and many other useful techniques

Subject matter is mostly well explained in the lectures

Original authors of a technique are cited

Bad points:

Some things should be explained more elaborately while other explanations can be shorter, especially in the assignments.

Mistakes in the editing in the audio clips of the lectures

Mistakes in the notebooks, sometimes non-intuitive/bad coding principles are used

von Devin F

Mar 11, 2018

For me, there was a large gap on time between when course 4 and 5 were offered (months). This unfortunately was enough for me to forget everything I learned about Keras.

Of course, this course assumes you know Keras so I was behind for the labs

Material is interesting though.

von Suresh D

Mar 26, 2018

I guess as the subject matter becomes more complex, more training is required on the underlying frameworks being used- Keras, TensorFlow etc. Did not feel that sufficient time was spent on understanding the underlying frameworks. Also the TA work is of spotty quality. But I love the way Andrew teaches.

von Parikshit D

May 27, 2018

The assignments are not very satisfactory..

von Yash R S

May 09, 2018

Not as great as the other courses in the specialisation. The assignments can be a little off putting, but lectures are top class again.

von Thomas N

Mar 09, 2018

Good subject, but a lot of the course material (like lecture slides and problem sets) was either unavailable or out of date.

von Benoit D F

Mar 19, 2018

Very interesting topic but coding exercices and quizzes were a bit clunky and in need for ironing

von Ramon R

May 08, 2018

Unlike the other courses which Andrew Ng provides, this one contains many spelling mistakes in the programming assignment, the programming assignments are less structured and understandable (missing or wrong information in nearly every assignment) and an introduction to keras is missing. I found it great that the keras framework is an important component of this course, but unlike the tensorflow introduction it is missing here. It is frustrating, when you might have the right functions but no information how to input and determine the correct variables for the functions. Anyway I found the outline of the course very good as it gives a good overview of many methods and how they work. To my mind the consistency of the assignments and also the story telling needs to be improved to reach the level of other courses where Andrew is involved. It appeared more chaotic and the complexity of the algorithms is overwhelming, so a better introduction to how they work, might be appealing. In the end, I worked through it and I gained a basic understanding of keras and RNN algorithms. So it was definitely worth it.

von Pablo M

Mar 18, 2018

Despite being a great introduction to many NLP concepts, the programming exercises are a bit too much "fill-in-the-blanks" and not challenging enough. It is still a great course !