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Отзывы учащихся о курсе модели последовательности от партнера deeplearning.ai

4.8
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Оценки: 27,223
Рецензии: 3,243

О курсе

In the fifth course of the Deep Learning Specialization, you will become familiar with sequence models and their exciting applications such as speech recognition, music synthesis, chatbots, machine translation, natural language processing (NLP), and more. By the end, you will be able to build and train Recurrent Neural Networks (RNNs) and commonly-used variants such as GRUs and LSTMs; apply RNNs to Character-level Language Modeling; gain experience with natural language processing and Word Embeddings; and use HuggingFace tokenizers and transformer models to solve different NLP tasks such as NER and Question Answering. The Deep Learning Specialization is a foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. It provides a pathway for you to take the definitive step in the world of AI by helping you gain the knowledge and skills to level up your career....

Лучшие рецензии

AM
30 июня 2019 г.

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.

JY
29 окт. 2018 г.

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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176–200 из 3,242 отзывов о курсе модели последовательности

автор: José D

6 нояб. 2019 г.

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)

автор: OMAL P B

10 апр. 2020 г.

I Highly recommended this course on Sequence Models. The course is easy to follow as it gradually moves from the basics to more advanced topics, building gradually. Andrew Sir makes the cocepts behind the scenes about LSTM GRU etc very easy to understand. Assignments are great, extremely well designed. Best assignments you will ever get to practise and learn.

автор: Hardik A

4 мар. 2019 г.

The kind of simplicity with which the course is explained and the amount of knowledge gained is worth the hard work of many months! . . I would like to thank the whole Coursera team and Sir Andrew Ng for creating such a wonderful platform and a big shout-out to all the mentors and community who have replied to the most basic queries in the discussion section.

автор: Bing H

27 июля 2019 г.

Home work assignment notebook has a quick time out issue. It's quite annoying since most of the assignment has lots reading material to fully understand the topic or method. Often the notebook just time out and has to be restarted before move to the next section. Hopefully, it can be fixed or improved.

Overall a very good course to learn about sequence model.

автор: Serg D

29 июля 2021 г.

This was truly an exceptional course on neural networks. Although created several years ago, i havent seen a better course on coursera yet. The course went through all aspects of all types of neural networks, was very detailed and explanatory, apart from the last week of the last course - transformers work. Highly advised for all machine learning engineers.

автор: Jiandong S

9 мар. 2019 г.

It took me a longer time to finish the course due to busy schedule. But I found it totally worth the struggle to work on the course material. Sequence modeling and processing is an new area to me. The course taught me some basic concepts and gave me a chance to lay hands on through programming exercises. I feel a lot like the topic particularly NLP. Thanks!

автор: Quentin G

14 авг. 2018 г.

Très largement plus difficile que tout ce qu'il y a eu auparavant. Un véritable apprentissage et un plaisir surtout sur le Trigger Word Detection qui était très intéressant.

Totally more difficult than anything before. I've acquired true knowledge that I'm very proud of. It was a pleasure, especially for the Trigger Word Detection which was very interesting.

автор: Lucas O S

17 февр. 2018 г.

Exercises too basic. Better to do something simpler from scratch, them fill in the blanks on statements like "define a to be a boolean variable initialized to True", and run a bunch of other cells with imported code that hides the actual complexity. These kind of exercises does not add anything to the student. Content of Andrew's lessons is great, however.

автор: Neelesh A

25 мар. 2020 г.

This course helped get a good intuition as well as further specifics of voice recognition which is what I am most curious about.

I think they have put together a right mix of Conceptual puzzles, Implementable codes and Lucid lectures to help one learn and advance one's understanding and intuition framework to build on top of subsequently.

Great work guys!

автор: Gaurav K

23 мар. 2018 г.

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!

автор: Shifeng X

7 апр. 2018 г.

awesome! Thanks to Andrew and his time to deliver this wonderful course. It really give me a very good sense about what's going on with the Deep Learning in several areas. The course material is prepared in a way that it's very easy to catch up. Just one suggestion, this sequence model session is too short, lots of topics haven't got well deployed.

автор: Martin B

22 мар. 2019 г.

Very very interesting but it's a lot more difficult than the other courses. I did it out of sequence (no pun intended) (i.e. I skipped Convolutional networks to go straight to RNN, because they interest me more).

That wasn't the correct move. I barely knew anything about Keras, the exercises took a LOT more time. Still, it's a wonderful course.

автор: Alison

23 июня 2020 г.

The class lectures are easy to follow and programming practices showcase a good variety of interesting implementation/practice of sequence models. Not only does it introduce how models work and are constructed but also illustrate how those models can be applied to real-life problems (e.g. voice detection in smart home, music generation...etc.,).

автор: Dhruv B

6 июня 2020 г.

I have earlier completed first 3 courses of the Deep Learning Specialization. This course widens the horizon of deep learning applications. Through the assignments, I have gained confidence in understanding the model architecture and the underlying theory behind it. I recommend every to enroll for this course if they want to learn how RNN works.

автор: Wei H

10 июня 2018 г.

Great lectures on the intuitions behind RNN and their applications in real life. It requires some self-exploration to complete the programming assignments related to Keras and tensor, but the structure of the assignment is very good. I have learned a lot from this lecture and it helped me to understand the language of the field of deep learning.

автор: Pablo G G

10 сент. 2020 г.

Awesome course, with lot of detailed and well guided practices! After finishing all of them I went directly to look on GANs and Transformers and with the knowledge gain thanks to Andrew Ng and his team, I set up my local Jupyter with tensorflow-gpu and start using state-of-the-art machine learning! Check out paperswithcode for awesome projects!

автор: Nikhil D K

14 мая 2020 г.

I decided to do this course after reading the first few pages of the Deep Learning book by Goodfellow, Bengio and Courville. I'll probably go back to that book now, to reinforce what I learnt from this set of 5 courses. I plan to also get more practice with the programming frameworks. The Tensorflow specialization is probably my next conquest.

автор: CH L

22 мар. 2020 г.

This course is really fantastic. It teaches several of the most important contemporary applications of deep learning, and mentions lots of important points of these models.

The assignments are amazing. They are easy but still able to make sure you've gone through the whole design of models.

Definitely one of the best lectures I had in my life.

автор: Andrii S

26 окт. 2020 г.

Many thanks to Professor Ng, this is absolutely the best online course that I've taken. It is fantastic how much value he creates for all of the learners, conveying very complex ideas from the world of deep learning in a simple and understandable way. I hope one day I will meet Professor Ng and thank him in person. An amazing specialization!

автор: Alam N

27 янв. 2019 г.

Finally, after 6 months achieved desired goal in Deep Learning Specialization.

Thanks to #andrewng #coursera team for motivation and opportunity. It was not possible but due to #andrewng motivational words and explained deep knowledge in simple words. I can't express my feeling in words. Thanks again

Best wishes for Andrew Ng and Coursera Team

автор: juan m e b

21 мая 2018 г.

Excellent as always. This subjectcould easily take more weeks or even months to understand, but Andrew explains complicated concepts in very easy terms. Though sometimes it seems a bit esoteric and magical, due to how easy he makes it sound, it's a great start point to begin to investigate, read and implement the most important algorithms.

автор: Claes P

8 мар. 2018 г.

This course challenged me. It forced me spend more time on the things you really need to understand before moving forward. Frustrating of course, but the reward is golden. It also tells me I need to learn more Keras. I was really inspired by the exercises, by all the things you actually can create by using the superpowers of deep learning.

автор: Alexandre C

22 февр. 2018 г.

Excellent. I am doing a research on LTSM application for process plant data and asset health prognostics and the materials I found on the web were usually a bit "dry". The course enabled me understanding the concept mechanics and keras code basics to start using on my own applications - What else I could have asked for :D ?

Cheers/Alex

автор: Anurag W

10 июля 2020 г.

I had a lot of fun doing these courses and weekly programming assignments.

Mr. Andrew Ng is a great instructor, he does a great job of explaining the neural network architecture and helps create an intuition behind difficult concept, these are really helpful at the end of each week when you are practising the programming assignments.

автор: Siddharth B

11 янв. 2019 г.

I am grateful to Professor Andrew Ng. and the entire team of deeplearning.ai for giving me the platform to learn, practice and showcase the deep learning concepts in such an elegant and concise manner. The journey has truly been educative and enlightening and I look forward to applying the concepts and skills in my further endeavors.