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25,078 Bewertungen
2,939 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. 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....



Mar 14, 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!


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.

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2401 - 2425 von 2,914 Bewertungen für Sequence Models

von Iain C

Oct 04, 2019

Some of the assignments are very difficult to pass. I think I understand the concepts but the instructions for the assignments could be a lot clearer and provide more guidance.

von Gregory S

May 26, 2020

Excellent content, although the exercises - at this stage of specialization - should focus more on NN architecture, than on pure computational and matrix slicing tasks, imho.

von Kaan A

Aug 12, 2019

Even though it has some flaws in audio clips and homeworks, programming assignments are fun to do. Great real world applications on this whole specialization is just perfect!

von Lap-hang H

Sep 09, 2018

The content was quite good as with previous courses in this specialization. Just dropping a star because week 1 material wasn't as clear to follow as the rest of the content.

von Juan Z

Nov 29, 2019

Compared to the first two sections, I don't think this section is better than those. Anyway, I learnt some concepts about sequence models which I need to dive into in future

von Tang Y

Apr 11, 2019

The videos are of high quality as always, while the programming exercises had some error in it. Compare with the previous few courses this one seems not polished so well.

von David J

Feb 18, 2018

Thank you Deep learning team for putting together this course. The course has really helped me understand the various possibilities with the knowledge of deep learning.

von Bhavul G

Dec 31, 2018

The first week was a bit too tough compared to the second and third. So, I felt it was a bit hurried. It could have been distributed into two separate weeks, perhaps.

von Cristhian P

Jun 29, 2018

This course was very useful. I would make the programming assignments for the first session a bit clear. Other than that, everything was easy to understand and clear.

von Mike

Mar 16, 2018

Good, but not as in depth as the other lecture series I found. It is faster paced and skips over much more of the detail at which they go into in the earlier modules.

von joris b

Feb 15, 2018

If the programming exercises weren't plagued by some bugs, I would have given 5 star. It's a very complex subject matter, but Andrew takes you through it by the hand.

von Robert L

Aug 28, 2020

I feel week 2 and week 3 materials were covered a bit too quick. Would appreciate more explanation of the implementation details of beam search and activation model.

von Amir A

Aug 31, 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.

von Jürgen R

Apr 04, 2018

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

von dang

May 22, 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.

von Tom S

Apr 26, 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.

von Tim A

May 15, 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.

von Yogeshwar D

Apr 29, 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

von siram n

Jun 06, 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.

von rohan S

Dec 17, 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

von nitin s

Jul 11, 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

von Cazaubieilh G

Mar 18, 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

von ignacio v

Oct 18, 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

von Péter D

Feb 08, 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.

von Matheus H B d A

Feb 04, 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.