Chevron Left
Voltar para Sequence Models

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

4.8
18,211 classificações
1,973 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

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.

Filtrar por:

326 — 350 de {totalReviews} Avaliações para o Sequence Models

por 黎功福

Mar 11, 2018

Thanks, Andrew.

Good job!

por Pankaj J

Mar 05, 2018

Great course, you guys have done it again :)

por Emilian A

Apr 16, 2018

I find CNN/RNN courses very helpful, but I would highly recommend to improve the exercises. Some typo mistakes can result in hours wondering what is wrong.

por Chertushkin M

Apr 01, 2018

Fantastic!

por Oleksandr M

Feb 09, 2018

Great course! As always, there are interesting lectures, useful assignments, etc.

por wangdawei

Mar 30, 2018

por Fabian M

Mar 14, 2018

Thank you for creating a course that provides so many insights into such a difficult topic. Were it not for this entire specialization I might still be lost looking for a way to enter the field of AI. Thanks a lot!

por Piyush B M

Mar 27, 2018

Would be great if you could add a week on time series analysis, modelling and forecasting.

por Zein S

Feb 15, 2018

This is not a good course, and even not a good tutor.. It is a great course and Andrew is really incredible tutor... I like this course so much and got tons of benefits...

I am so happy to take this course..

PS: You can add this review to the sentiment analysis data set

por Nand K p

May 07, 2018

Superb course material! Eventful learning experience! Thanks a lot Andrew!

por Anand R

May 07, 2018

To set the context, I have a PhD in Computer Engineering from the University of Texas at Austin. I am a working professional (13+ years), but just getting into the field of ML and AI. Apologies for flashing this preamble for every course that I review on coursera.

This course is the 5th and final one in a 5 part series offered by Dr. Andrew Ng on deep learning on coursera. I believe it is useful to take this course in order and it makes sense to study it as a part of the series, though technically that is not necessary.

This is one of the best courses to take if you want to understand the basics of Sequence Models (Recurrent Neural Networks). RNN is a technically-difficult-to-understand, still-evolving field of Neural Networks, and it has thus far found remarkable uses in a wide variety of field, ranging from Natural Language Processing (NLP) to Voice-to-Text conversion and Music Synthsis, to name a few. Dr. Ng really exposes us to this cutting edge research, by explaining research papers that were only recently published. By now, I could see how the problems would be tackled. However, there are several subtle aspects, such as the optimal metrics to use, the clever modification in the NN architecture, etc. which Dr. Ng drew attention to and made clear.

The instructor videos are very good, usually 10 min long, and Dr. Ng tries hard to provide intuition using analogies and real-life examples. The quizzes that accompany the lectures are quite challenging and help ensure that the student has understood the material well. As with the other courses, the programming exercises are the best part of the course. You get to practice, (1) Music synthesis, (2) NLP and Sentiment Analysis, (3) Trigger Word Detection (Hello Google, Hey Siri, Alexa!), ... All these problems are actual, real-life projects, which are extremely difficult to solve. They help the student practice the strategies and also provide a jump-start for the student to use the code for their own problems at work or in school.

Overall, this is an excellent course. Thank you Dr Ng and the teaching assistants, Thank you coursera.

I HAVE A HUGE GRIPE WITH COURSERA's TECHNICAL SUPPORT. THEY DO NOT HAVE A READILY AVAILABLE TECH-SUPPORT EMAIL ID. YOU HAVE TO SEARCH THROUGH THE WEBSITE CAREFULLY TO FIND A CHAT LINK. I HAVE RECOMMENDED COURSERA TO SEVERAL FRIENDS AND MANY OF THEM ARE VERY UPSET AT THE SUBSCRIPTION POLICY, WHICH IS SNEAKY. IN FACT THE WORDING IS ALMOST DESIGNED TO CHEAT YOU.

I have been a huge supporter of Coursera and hate to give this negative feedback here. I would have easily subscribed to many other useful and important coursers that Coursera offers, but will now be doubly careful about doing so.

por Frank T

Feb 20, 2018

I think it is a great course. There are some issues here and there with notebooks and related materials. However, considering the large and detailed amount of content in this course and it being a new course, things not being 100% perfect is OK by me. I would rather have the thoughtful content and exercises, versus something much lighter that would be easier to produce. Thank you to all who prepare these courses.

por Gaurav K

Mar 23, 2018

Thank you Prof Andrew Ng for sharing the knowledge and experience. It has been truly a great learning during the course specialization. And I always admire the way you structure the course and teach the advanced concepts with such an ease. With the power of AI, we as a community try to solve real-world challenges for better life. Thank you so much!

por Michael D

Mar 23, 2018

Worthwhile conclusion to the deep learning specialization.

por Vivek S

Apr 15, 2018

Excellent course for beginners. Andrew NG and team has done tremendous job by putting together all those contents together.

por Jie Z

Mar 20, 2018

Excellent

por Solomon W

Feb 12, 2018

Very frustrating grader. Really time wasting. What is this team trying to accomplish with such disorganized efforts? I hope to see more improvements in the future. I have just completed week1's assignments and revising my reviews from 1 to 4 because the course content is really good and has softened the disappointments caused by the grader.

After week1, the grader frustrations eased as it was working more and more consistently. Most importantly, I learned lots of cool stuff and so I am revising my reviews from 4 to 5. I hope all grader issues are now resolved.

por vasu k

Mar 26, 2018

Excellent course with great assignments

por Kelvin K

May 22, 2018

Very clear and easy to understand.

por Zeev S

Feb 11, 2018

practical with reasonable theory depth of the theory behind. Good exercises.

por Tejas L

Feb 18, 2018

What an amazing course!

Week3 assignments blew my mind! Some core engineering problems too

por Joel G

Feb 15, 2018

Entertaining and precise

por Yunfei D

Apr 15, 2018

I've learnt a lot from this series.

por Jiansen.Zheng

Feb 14, 2018

Pretty good, for learning recurrent neural network and neural machine translation, and I learned a lot about Keras in the program assignments.

por Luis A H G

Feb 26, 2018

Excellent course. Very practical with a lot of coding exercises.