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Comentários e feedback de alunos de Sequence Models da instituição

15,889 classificações
1,741 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. 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


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.


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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101 — 125 de {totalReviews} Avaliações para o Sequence Models

por Hari K

Nov 27, 2018

Andrew makes the topic interesting and easy to grasp. The assignments are very well written. Great course!

por Frank Z

Nov 13, 2018

Very great class

por Rajan K

Nov 13, 2018

Thank you for introducing RNN briefly. This is a vast topic but the course managed to give a good idea to enable one to begin on RNN modelling. Thank you Andrew!!


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.

por Fernando E L M

Nov 12, 2018

Excellent course. The content and theory were heavy but gratifying once completed. I recommend this RNN training course.

por Xiaoahe X

Nov 29, 2018

The course is really helpful, but It takes some time to get familiar with Keras.

por Jeremy L

Nov 30, 2018

Really useful for learning NLP and Audio processing!!

por Shithi M

Nov 14, 2018

A wonderful, intellectual experience!

Don't fret if you are having to look up a few documentations, the comprehensive documentations of the built-in functions/layers needed are accessible on the official websites of the libraries(Keras, NumPy).

por Satyam N

Nov 14, 2018

Doesn't hide the math behind concepts. Provides a very detailed explanation of topics covered. Assignments are fun to do.

por Edwin Y

Jan 16, 2019

Thank you Andrew and the team for putting together such a great learning experience.

por Kirk B

Jan 17, 2019

Andrew Ng is hands down the best teacher in this space. Excellent lectures and a well run course.

por Babu, C

Jan 07, 2019

Can't get better than this in academic world! Outstanding practical examples given. Very happy to be hands on this course

por Juandiego M

Jan 05, 2019

Another fantastic class by Andrew Ng! I learned a lot in this class, and in the Deep Learning Specialization in general.

por Ali S

Jan 05, 2019

Finally, I understood LSTMs, thanks to this course, thanks to Andrew! Before this course, I spent many hours reading papers on LSTMs and trying to figure out what is going on with all these "Gates", but couldn't understand intuitions behind them. In this course not only I learned and understood them, but also I learned a lot about machine translation and speech recognition which I was frightened to approach them. This course gave me all fundamental concepts and tools that I needed to be able to deal with sequential data.

por Yusri D H

Jan 06, 2019

The course is very fun and clear.

por Tian Q

Jan 06, 2019

Great content! Andrew's lectures are great as always. The assignments are absolutely exciting and fun. Obviously the team put a tremendous effort on the programming exercises to make them doable for laymen yet not trivial. The exercises avoid using libraries (like Keras and TensorFlow) at the very beginning. Instead, they started with the more basic Numpy implementations. After these practice, I am able to grasp what each layer is actually doing.

My only suggestion is to correct some trivial typos in the Notebook.

por Vladimir L

Jan 05, 2019

This is a great course, it gave me a good overview of how various types of data (written text, speech, images/video) are used in neural network models. The course materials smartly omit complexities behind pre-built deep learning models, and provide students with hands-on examples, which spark creativity and imagination. Thank you!

por Moayyad A Y

Jan 18, 2019

One of the best courses in RNNs and i have seen many.

por banafsheh

Jan 18, 2019

the first week is relevant to my work, but it was great learning a bit about other topics in week2 and week 3. Thank you so much for making these videos and assignments!

por Hussain M A

Jan 18, 2019

Its a good course to understand sequence based models.

por Ramesh N

Jan 19, 2019

Systematic, step by step approach to understanding sequence models and practical exercises to see them implemented with lots of guidance.

Thanks you!

por Kak S

Jan 20, 2019

Great and excellent

por Nishant S

Jan 09, 2019

Great course. Andrew is the best teacher ever!

por Rahul D K

Jan 08, 2019

Very helpful course

por Lucas G S P

Jan 21, 2019

I appreciate all the hard work and effort Andrew and his team puts in all his material.

I had hard time with most of Keras homework’s, I think it's hard to get the overall logic of a framework without an extensive explanation.

Besides that, the topics discussed are amazing.