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Отзывы учащихся о курсе Sequence Models for Time Series and Natural Language Processing от партнера Google Cloud

4.4
звезд
Оценки: 471
Рецензии: 66

О курсе

This course is an introduction to sequence models and their applications, including an overview of sequence model architectures and how to handle inputs of variable length. • Predict future values of a time-series • Classify free form text • Address time-series and text problems with recurrent neural networks • Choose between RNNs/LSTMs and simpler models • Train and reuse word embeddings in text problems You will get hands-on practice building and optimizing your own text classification and sequence models on a variety of public datasets in the labs we’ll work on together. Prerequisites: Basic SQL, familiarity with Python and TensorFlow...

Лучшие рецензии

PR
10 авг. 2019 г.

Great way to practically learn a lot of stuff. Sometimes, a lot of it starts to go over head. But, it is completely worth the learning curve! Definitely recommend it!

AJ
7 июня 2021 г.

The lack of synchronization between the videos and labs is extreme in this course, but the lectures are excellent and the subject area covered is very broad.

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1–25 из 66 отзывов о курсе Sequence Models for Time Series and Natural Language Processing

автор: vincent p

24 февр. 2019 г.

Several exercices do not work as described, with error messages.

Explanations of what we are doing are light.

автор: YUNWEI H

20 февр. 2019 г.

Too focused on GCP. Could be more on DL itself.

автор: Temuge B

26 апр. 2019 г.

Videos were too short. Explanations of the key concepts were really poor. Quiz in week 1 had error that was raised by the user 6 months ago and it is still not fixed. Coding section had library mismatch that led to errors. The presentation of the materials were good.

автор: Serg D

27 окт. 2019 г.

Maybe this course was too advanced for me. I did the other course on tf and that felt too easy. This was unreasonably hard. There was no explanations at all before labs and there were like 5 labs a week. how are we supposed to do them? i skipped nlp entirely, because i could not follow it at all due to zero guidance and explanations. The only skill i got from this course was to copy code from internet, but i could do it before

автор: Harold M

25 нояб. 2018 г.

This was a very interesting course on NLP and Time Series. My only concern is that some notebooks worked for python 2 mode and not for python 3. Also, the tensor 2 tensor lab could not be completed in 2 hours, as some of the training may take more than 3 hours to complete.

Overall, good information, great technology and great teachers.

Thank you.

автор: Maxim

5 июля 2019 г.

One star, but not to content. But because the course don't have "Audit" option. It's mean that after subscription ended and you received certificate, You can't more access to video material in course. When subscription active, You can use mobile application and download video material for studying offline. Before yours subscription ended, copy video material to safe place for later review.

p.s.

But the course content deserves a higher mark - 4-5 stars. As others courses in this specialization

автор: Jakub B

26 июня 2019 г.

Subscribing to this course only gives you option to run assignments on Qwik labs, and they're very poor for these kinds of assignments. You won't get any feedback on assignments anyway since there is no grader.

If you want to check out the material it's better to just clone training-data-analyst from github and do these assignments on GCP free tier.

автор: Arindam G

20 дек. 2018 г.

No Doubt COURSERA is always best AND MNC like IBM,Google courses associated with coursera are MIND-BLOWING.

The Instructors are so great at Explanation Part that hardly anyone won't Understand All the Topics

I would love to thank all the INSTRUCTORS who created such a Awesome Content for us.

My Personal Ratings For All the Instructors: 100 / 100

автор: Antony J

8 июня 2021 г.

The lack of synchronization between the videos and labs is extreme in this course, but the lectures are excellent and the subject area covered is very broad.

автор: Jun W

10 нояб. 2018 г.

Excellent course for those who know RNN. Knowledge is refreshed and techniques are consolidated. More details about Google ecosystem is introduced.

автор: Ben

11 янв. 2021 г.

Tutorial content frequently doesn't match that described in the videos.

Some introduction to machine learning concepts but often pushes you to a Google automated version of it rather than describing the principles in much detail.

Issues with tutorial content being incorrect has been flagged for a long time - comments in the forum go back many months, but nothing has been done to correct it. Videos also reference content not present in the course, feels a bit cobbled together from other courses. One package taught is now also described as deprecated on its page Appreciate software moves quickly but considering it is a Google package you'd hope they'd keep up to date on that.

I enjoyed the introduction to a range of topics in the area especially RNNs and encoder-decoder but the issues with the labs significantly detract from the merits of the course.

автор: Prajwol L

11 мая 2020 г.

Why dont you make a easy lab works ? I mean the procedure is too much. As simple like Andrew Ng's course would be great.

автор: Navid K

1 янв. 2020 г.

Amazing course, I also took a bunch of other Deep-learning and specially Sequence Modelling courses from other renown instructors and institutions. However, this is so far the best. better than all of them.

1- Very well structured

2- Fairly advanced in contents and techniques

3- Reasonably challenging.

4- Full free access for a trial period ( not all courses offer that)

5- Access to GCP for free

Amazing course, well done Google

автор: Carlos V

3 февр. 2019 г.

Excellent Sequence Models explanations and examples to learn from, I quite enjoyed all the fantastic tips and best practices recommended by Google, looking forward to the next course in the specialization.

автор: PLN R

11 авг. 2019 г.

Great way to practically learn a lot of stuff. Sometimes, a lot of it starts to go over head. But, it is completely worth the learning curve! Definitely recommend it!

автор: Nebojsa D

29 февр. 2020 г.

I have only one remark, please improve lesson regarding NLP by includin model build etc.

Otherwise course is excellent and was helpful for me

автор: Ayman S

17 авг. 2019 г.

I like it because it is very relevant to my work. The dialogflow part is a bit weak. I am not sure if it is the product or the course.

автор: zios s

16 дек. 2019 г.

Awesome course, Great tutors they teach tough topics very easily like RNN(LSTM, GRU), Encode Decoder and attention.

автор: Youdinghuan C

14 июля 2020 г.

This course is short and sweet, and covers many helpful usecases of GCP tools related to the course topic.

автор: Md. A A M

19 июля 2020 г.

Everything was fine except the solution videos are old, that why you should update with update code.

автор: 林佳佑

2 нояб. 2018 г.

this course is helpful for learning sequence data with tensor flow ,Thanks for this course

автор: Mark D

2 февр. 2019 г.

Very good.The explanation of the RNN was very good but the tensor2tensor was very hard.

автор: Armando F

31 мая 2019 г.

Lot's of good information. I cannot wait to start using this knowledge. Thank you!

автор: Mahmmoud M

26 мар. 2020 г.

A Very powerful course

Thanks for all google team

автор: Enrique A

26 окт. 2020 г.

Mil Gracias Google, Mil Gracias Coursera.