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

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2,207 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

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.

SB

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!

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101 - 125 von 2,185 Bewertungen für Sequence Models

von Kostas H

Nov 05, 2019

The best online course I've seen anywhere about recurrent neural networks! Prof. Andrew Ng explains everything in such a simple manner. For example, understanding the structure of LSTMs is quite challenging, but Prof. Andrew Ng explains it in a very easy to understand fashion. Likewise with GRUs, Seq2Seq models, bidirectional RNNs, etc. And the code exercises have very beautiful and detailed explanations.

von Guruprasad S

Mar 05, 2018

Thanks Professor Andrew Ng and team for the deep learning specialization. The course material was well designed for online learning. The assignments were perfectly manageable with a few hours of investment every week and the learning was very effective. Last but not least, I found Professor Ng's wisdom, insights, tips to be invaluable to anyone regardless of their level of expertise in machine learning.

von Shishir M

Dec 31, 2019

This was the best course among 5 course specialization. It was well designed, structured and application oriented. Assignments were pretty fun to solve as they involved solving real world problems. This course gave me direct exposure to industry level problems and helped me gain more insights towards the future of deep learning. Because of this I am really excited to continue working in deep learning.

von Rohit K

Jul 06, 2019

Hello Andrew, I am a big fan of you. Learning from your every course. Very unfortunate that I can do that remotely only.

One thing that I want to mention - Can we have lecture notes on coursera, just like the way used to in CS229 that we can read before coming to next lecture. I found that that was very useful in understanding when things get harder.

Thanks hope we can improve coursera in that matter.

von Daniel C

Feb 16, 2018

The Sequence Models course covers state-of-the-art deep learning methodology as of 2018. The instructor is awesome. The assignments help solidify concepts presented in lecture videos. One nitpicking comment. This course, being relatively new, was less polished compared to the other courses in Deep Learning Specialization. I'm sure future updates will eliminate glitches and errors in the near future.

von Raimond L

Jan 11, 2020

Good course to help you understand how sequence models work and how to apply them for various problems. Majority of topics are explained quite well. Practical problems sometimes could be a challenge, but every problem has hints and a bit of theory provided. Overall this course was a very positive experience and I do recommend it. Special thanks for the people who made this course possible.

von Dmitry T

May 03, 2018

I liked that this course was a bit harder than others in the specialization (well partly because It felt like notebooks were made in a bit of hurry here) but it was a good thing for me, since I had to think more on the programming excercises, read Keras documentation, derive backprop equations - and I believe such engagement with the topic really allows to understand and remember it better.

von Mary A B

Mar 19, 2018

It's been so rewarding to apply what I've learned in the previous courses of the Deep Learning specialization to time-based problems. I feel I have a better understanding of how some of the "magic" technology like virtual assistants and speech recognition work. While the material in the first four parts was also very useful, the specialization would have felt incomplete without this course.

von Leandro O B

Jun 04, 2019

Another outstanding course about Deep Learning.

It teaches Recurrent Neural Networks from the basics up to industry applications such as Speech Recognition and Natural Language Processing. The programming assignments are extremely useful to build strong understanding of the algorithms, which we code "from scratch" with NumPy before using higher level frameworks such as TensorFlow and Keras.

von Abe E

Mar 09, 2020

It's a great class, and Andrew Ng is a great instructor. I wish the exercises were a bit harder. Since the course is aimed at all and I am coming from a graduate degree in the sciences, I realize it's hard to cater to all educational backgrounds. I would have liked to see optional/honors exercises to get us more involved. Other than that, I loved the class. Thanks so much for teaching it.

von Simon R

May 13, 2018

Loved the course, Andrew is a great teacher; very impressive ability to explain and give intuition. I can really see how I can build upon this course to help me in what I am doing at work. I think there is definitely some room to go deeper on some of the topics e.g. don't just teach sequence to sequence but also broader uses of recurrent networks. Maybe a follow-up course? ... please???

von Fabrice L

Jul 18, 2018

This module of the specialization is a bit more complicated than the others; at least to me, I found the concepts more difficult to grab.

Anyway, thank to Andrew and his team for this amazing specialization. The lectures are great, the assignments are fun and have interesting examples. A huge amount of knowledge along all the courses. You can tell there is a lot of work behind it.

THANKS

von Apoorv V

Jan 03, 2020

I was about to give this course a 3-star rating unlike the other courses in the specialization, which I have rated 5 stars. The reason for that was the programming exercises in week 1. They are not interesting and do not impart a lot of learning. Please consider improving those. The reason I still gave 5 stars is because of the amazing programming exercises in weeks 2 & 3. Thank you.

von JC Q

Feb 10, 2018

In the continuity of the 4 previous modules, the Sequence Models course is of very high quality, the material is concise but cover a wide range of applications and methods, and is delivered with consistent clarity. The programming assignment gives very good hands challenges. I highly recommend this course to anyone interested in natural language processing or speech recognition.

von Mashrur M

Jun 30, 2019

This is the last course of the Deep Learning journey, and I felt like a learned a lot in it. Sequence Modelling is a different beast compared to non-time series models, but I've mastered it thanks to this course nevertheless. I would recommend this particular course to anyone who has a moderate understanding of deep learning and wants to get into time series analysis and nlp.

von Peter V

Sep 12, 2018

A succinct overview of a number of ideas in sequence models. Some of these were covered in an NYU course I took 4 years ago (embeddings, LSTM), others I had heard about but hadn't had a chance to look into (attention). The assignments were set up to be pretty easy, but I think trying to do them from scratch rather than by filling in code would make for a pretty good project.

von Guy M

Sep 05, 2018

Great introduction to sequence models/RNNs. The real-world examples were very illuminating. Again, as with the previous course in the specialization, I felt some details of how to run/predict NNs using keras were lacking, which could leave a student floundering if they've never used keras before. This is in contrast to some other, much easier, tasks where hints were given.

von Alexander G

Feb 25, 2019

Out of 5 courses offered I think this was the most exciting one as it combines everything learnt so far and teaches how to combine different NN modeling techniques to achieve desired classification/prediction features . For example, it is pretty much clear how one would go about building an app that would describe a picture to blind people and do that in many languages.

von Kévin S

Jul 31, 2018

This short 3 weeks courses will make you work a little, exercice take at least twice the time write. You will learn about the famous LSTM, and how to use it on various tasks.

I'm not sure the 'translation' tasks is a good example but there is lot about it. Not a good example, because it is not state of art, and in the 'translation' business there place only for the best.

von Yogeshwar S

Apr 01, 2018

This is a great course, and a great specialization. The professor explains the concepts across very well, not only in this course but in all courses of the specialization. My only gripe is with the notebook/hub/grading system which especially in this course has acted strange and cost a lot of time. That said I've learnt a lot, and am quite happy with the course content.

von SUJITH V

Nov 13, 2018

Great course overall to learn the basics of sequence models and also get a brief understanding of the state of the art architectures used currently. The programming assignment on trigger word detection gives an insight into the practical machine learning implementation for speech recognition. This course combines both theory and practical advice in a very good fashion.

von Meynardo J

Feb 06, 2018

Excellent course - and specialization! Andrew Ng's special talent is in being able to explain complex and difficult stuff with such clarity that you can actually understand it and follow. I found the exercises in this course tougher than in the previous four, but they were varied, useful, and FUN! Highly recommended to all who what to learn the "deep" in Deep Learning!

von 向金芳

Jul 03, 2018

Because my research direction is NLP, so I think this course is very good for me. I learn how to implement the Sequence model such as machine translation 、Attention and so on. But the disadvantage is that there is no whole sequence model process. For me, The bigger problem is data processing and model. overall ,This course is good for me, I learned many from this.

von Matías P B O

Sep 10, 2018

The whole specialization is excellent. I highly recommend doing it. The only minor comment that I add is that Andrew should include some links for further reading (along the courses for each topic or theme). I know that anyone can quickly look up for them in the Internet (and they can be outdated) but that would make the specialization even better in my opinion.

von José D

Nov 06, 2019

This is Course 5 of the Deep Learning Specialization, and the last one. We learn Recurrent Neural Network (RNN) /Sequence Model, which allow translation or trigger word (like "Hey Siri!"). It's a completely different beast than CNN seen in Course 4. Again, nice videos and explanations, and well-designed useful programming assignment (TensorFlow/Keras and numpy)