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Comentários e feedback de alunos de Sequence Models da instituição deeplearning.ai

4.8
estrelas
22,855 classificações
2,637 avaliações

Sobre o curso

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....

Melhores avaliações

WK

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!

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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176 — 200 de 2,617 Avaliações para o Sequence Models

por Jonathan L

Dec 18, 2018

Great lectures on the different structures of Sequence Models for use in Natural Language Processing, Text Translation, and Audio Recognition. There is a lot of material packed into 3 weeks, but this course will help anyone familiar with Deep Learning/CNNs to take a dive into the world of NLP and audio/speech recognition.

por Harold L M M

Dec 10, 2018

This Sequence Models and RNNs course was a very challenging course in the specialization similar to that of Convolution Networks. I've learned a lot on these topics, and I will continue expanding my knowledge from here on.

Overall, this is a great and complete specialization on Deep Learning.

Thank you professor Andrew Ng.

por Himanshu S

Jun 07, 2019

The topics covered in this course were a bit on the advanced side. The technologies used are most frequently used in the area of NLP. The course helps understand the basic concepts of NLP like word vectors and embedding, at the same time explains the very complex concepts like LSTM, GRUs and Attention models very well.

por Uday K B

Dec 13, 2019

This course is perfect to learn deep insights of natural language processing, word2vec, speech recognition, trigger word detection and sentiment analysis among others. This course not only trains in using open-source libraries, but also trains to learn how to implement these life-changing techniques all by ourselves.

por Sharath G

Feb 22, 2019

Deep learning specialization is one of the best courses I've ever done. When I used to work on Computervision prior to this course, I used to stumble a lot conceptually and in implementation. This specialization gave me a pragmatic insight into the DL. Can't thank coursera, deeplearning.ai and instructors anymore. :)

por Sanket D

Jun 01, 2020

This course gives an in depth explanation and intuition of RNNs used for learning tasks involving Sequences.

The time required to complete programming assignments takes usually more than an hour to complete than the specified time.

Rest it was a very exciting journey to learn deep learning along with Andrew Ng sir!

por Anne G

Sep 13, 2019

I have thoroughly enjoyed the course from start to end! Each course is well organized, the teacher taught really well, and the programming assignments are very rich with easy to follow guidance, and lots of good libraries / functions that we can leverage / learn from. Thank you very much! Have a wonderful day!

por jaylen w

Nov 08, 2018

Finally I finished the whole series of Deep Learning AI, through which I gained a lot of intuition of deep learning algorithms and its implementation. It's great course to get into this new era especially with a excellent teacher like Andrew who really illustrates the core ideas of deep learning algorithms to me.

por Pavel K

Mar 31, 2018

The last module is awesome as all previous ones. Thank you all guys!

Thank you guys who posted questions, thank you guys who posted answers as well. I appreciate you all. And one more special appreciation to Andrew Ng for this entire course. This course gave me a great knowledge and intuition about Deep Learning.

por Rajan A

Jun 23, 2020

I have been through wonderful journey of learning and implementing deep learning from very scratch. This course really transforms one from caterpillar to butterfly with very minimal pain of calculus and linear algebra. Thanks to Andrew and deeplearning.ai team for providing such a marvelous bundles of knowledge.

por Sardhendu M

Feb 10, 2018

Lots and Lots of knowledge and experience in 3-weeks of class. In Machine Learning terms, this course maximizes the knowledge and experience gained with sequence models by minimizing the time required to complete the course. Lecture videos are very intuitive while assignment projects are very real-world centric.

por Matei I

Mar 31, 2019

Really good choice of topics, including state of the art tools like attention and word embeddings. Very useful, especially for those interested in Language Processing applications. However, the videos and assignments need some more careful editing, because there are occasional mistakes, lazy explanations etc.

por Maryam H

Jan 20, 2020

Very great and aspiring course, I learned lots of concepts in this course. I think It would be better If there was a capstone project for the final course of deep learning specialization. It was very great but If I had the opportunity of implementing a project from zero to 100, It would be more than great...

por Александр

Sep 02, 2018

Great course, though not as awesome as other Ng's courses. I think creators became a bit tired closer to the last course in specialization. Anyway, fantastic courses, fantastic specialization, fantastic professor! Thank you very much!! Looking forward to new courses - maybe Reinforcement Learning, GANs? =)

por Shabie I

Feb 18, 2018

Leave it up to Mr. Andrew Ng to explain complex concepts in a very much intuitive manner. The guy is a world apart when it comes to explaining complex concepts. No other MOOC even comes close. Absolutely highly recommended.

The only negative part about this course is that it ends. You don't want it to end.

por J.-F. R

Feb 18, 2020

Great course by Prof Ng. I had taken his Machine Learning course a few years ago, so expected high standards of content and assignment preparation - I was not disappointed. Staff is very responsive and helpful in forums as well. I highly recommend it. Taken as part of the DeepLearning specialization.

por Irvin

Feb 08, 2020

I loved this course as wel, I had a little bit less time to advance as steadily as I did with previous courses. So I had a little bit of trouble getting the context back when starting again each time. The next steps for me are putting what I learned into practice and basing myself on what I learned here.

por Pavel K

Feb 05, 2019

This course offers a great introduction to the models: RNN, GRU and LSTM.

In addition, it illustrates the power of "Word Embedding" and "Attention Model".

The programming assignments are interesting, provide deeper understanding of the models, and show how simple it is to implement these models in Keras.

por Camilo G

Jan 26, 2020

With this course it's possible to conclude that recurrent neural networks are the most powerful variant of neural networks. Used in a many places, this course expleains ingishtfully how they work, what's the math behind them, and how different implementations function for different areas of research.

por Angad P S

Feb 17, 2018

Andrew Ng knows how to make people understand the problem, architect a solution and then map it to data. He does it very well. I am going to repeat his course again as I still believe there is something that I have missed and I need to follow him thoroughly. I want to understand and process like him.

por Xiang J

Nov 10, 2019

overall it is another great course, clear explain on the RNN, LSTM, GRU, etc. really like the assignment to implement RNN from scratch. assignments related to Keras needs "googling" outside resources, and there is still some keras homework to be done in order to fully understand the assignment code.

por Jampana b

Feb 14, 2018

Thank you very much instructors. I learnt both fundamentals of deep learning and application of them in simple and efficient way. I have been long and fruitful journey with Andrew Ng. I learnt sound mathematics required for deep learning, tensorflow software, applications of sequence and RNN models.

por 邓佳阳

Jun 08, 2020

非常感谢老师提供的课程,原本课程实验对LSTM有相关研究需求,该课程很关键的提供了相关知识点的教学,再次感谢老师和平台!

Thank you very much for the course provided by the teacher. The original course experiment has relevant research needs for LSTM. This course provides the teaching of relevant knowledge points. Thank you again for the teacher and platform!

por TANVEER M

Aug 25, 2019

I have always found difficult how RNN and LSTM works as theretically I was not getting a clear picture how it was working .The programming assignments helped clear my doubts and I got a clear understanding to a lot of extent how this mechanism is working and how it is useful in speech synthesis.

por Zhiming C

Jun 14, 2020

This course introduces the basic idea of RNN, GRU and LSTM models. They are obviously harder than the CNN models and the concepts are not so easy to understand. Thanks to the systematic introduction! Together wit the excises I can understand better the theory from the applications. It's great!