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

4.8
Sterne
25,012 Bewertungen
2,931 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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2326 - 2350 von 2,905 Bewertungen für Sequence Models

von Sajal J

Jul 22, 2020

I am rating this course 4 because It doesn't give any guidance about future career paths and next things to learn. The explanations are very good. I understood complex things like GRU, LSTM, Bidirectional RNN, attention model very well.

von Diego A P B

Mar 07, 2018

While a great introduction on RNNs, I felt there could be another week of lectures given the complexity of the algorithms being explained. Likewise, the programming exercises felt unpolished in some parts, like in the expected outputs.

von Luiz C

Feb 11, 2018

Very good. To make it perfect, would have liked it for the Assignments to have less bugs (cf. LSTM backprop), and a longer course with extra weeks to present LSTM in the context of prediction (finance, weather, pattern recognition,...)

von Michael M

Nov 02, 2018

Great course! only negative is that problems would really hold your hand. I don't think there is any way I would pass a whiteboard test on any of this (then again a course to get me to that level would have to be double this length).

von Joshua H

Jul 20, 2020

The course covers one of the most influential developments in deep learning in recent times, and does so in a thorough way, introducing majority of the relevant mathematics and methods necessary to build a variety of sequence models.

von Jaiganesh P

Feb 18, 2019

The course is really good if you want to get a good understanding on the basics of deep learning. It would have been great if the course had more hand's on assignments than fill in the blanks kind of assignments in ipython notebook.

von Rohit K

Jul 07, 2019

I learnt a lot from this course and the whole specialization. I am grateful to the mentors and instructors. If coursera gives me opportunity I can also be mentor for the specialization to help the newcomers through the assignments.

von Ghassen B

Oct 17, 2019

During the first week, I think that a deeper explanation of the matrices' dimensions throughout the NNs should be given. Indeed, this would be helpful to understand some concepts.

Apart from that, it was an awesoome course, thanks!

von Stéphane M

Jun 22, 2018

The course was good except first week. I did not learn as much as I would like from the programming exercises of week 1. It could be nice to have 4 weeks instead of 3 for this course. Taking more time to cover the week 1 material.

von Shrishti K

Jun 26, 2020

Everything is perfect, the teaching is excellent, the only problem is the jupyter notebook, its sometimes difficult to debug issues and takes a lot of time and is kind of vague as well in terms of application of the lectures.

von Abid

May 01, 2018

some topics not explained in detail. Not enough examples to understand some models completely. As an example, I didn't fully understand what are the parameters for the models, their shapes, and how they are used in the model

von Harry L

Jul 16, 2018

Overall it was pretty informational on introducing NLP to me. However, Keras was a little bit frustrating to learn at the beginning. I found out the forum was a very good resource to learn Keras syntax whenever I was stuck.

von Eric C

Jan 13, 2020

Great course! I do feel like I'm just scratching the surface of the types of applications that I can make. I think the coding segments still hold our hands a little too much, but you can't beat the clarity of the lectures.

von Nguyen H S

Oct 21, 2018

The course lecture is grade but I hope the assignment is better in guiding structure, something the explanation is hard to follow, and the assignment should include the transfer learning instead of using the trained model.

von Paolo S

Jun 08, 2019

This was hard to keep up with, maybe too hard. The assignments' difficulty also was on a different level then the lectures maybe there more time should be put into the lecture videos as it was the case for DNN and RNN.

von Aida E

Feb 21, 2018

The videos and programming exercises were very interesting and insightful. My only complain is some of notebooks for exercises include errors and it was just a time-wasting task to find the "trick" to pass the grader.

von Anshuman M

Jul 30, 2018

The content is well captured and Andrew really helps build the required intuitions. But, the assignments are too guided. There is no room to struggle for solutions which often proves to be the main source of learning.

von Prateekraj S

Jul 29, 2020

The exercises are too short and too basic for this course specifically. The task is a great learning experience but there is not much one would struggle with in terms of difficulty as there is too much spoon feeding.

von Ivan

Mar 18, 2019

Great video lectures, but practical assignments are a pain due to awful auto-grading system and programming expirience in Jupyter in general. Most of the time you'll be searching for an error that isn't really there.

von Jeffrey D

Mar 11, 2020

Programming exercises did show you quite a bit, but got complex enough that most of my time was spent reading and understanding the preamble than doing any programming. That being said it delivered on the promise.

von Salamat B

Sep 24, 2018

Course content is really good! However, I found it quite difficult to truly understand deep learning algorithms. However, it provides good glimpse of of sequence models and intuitions behind various useful models.

von Georges B

Feb 21, 2018

Great course and material, Andrew NG really know who to explain difficult subjects in an intuitive way. However, the course seems that it still needs some work (there are some bugs in the lectures and assignments)

von Mayank A

Jun 30, 2020

The NLP Section of this course is quite difficult to understand(The Notations are quite confusing as well as prior knowledge is required to understand) but other than that RNN, GRU, LTSM are explained clearly.

von Seungjin B

Sep 08, 2018

Week1 lessons are a little complex than the previous classes and there are gaps between ground-up python version and keras version of LSTM model. Keras will need to be taught a bit more in detail to follow up.

von Lester A S D C

Jul 29, 2019

This is by far the hardest course in the specialization. But it was explained well. My only complain is there were errors in the first programming exercise. All in all, I learned a lot in this specialization.