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Sequence Models for Time Series and Natural Language Processing(으)로 돌아가기

Google 클라우드의 Sequence Models for Time Series and Natural Language Processing 학습자 리뷰 및 피드백

474개의 평가
66개의 리뷰

강좌 소개

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...

최상위 리뷰


2019년 8월 10일

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!


2021년 6월 7일

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.

필터링 기준:

Sequence Models for Time Series and Natural Language Processing의 66개 리뷰 중 1~25

교육 기관: vincent p

2019년 2월 24일

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

Explanations of what we are doing are light.

교육 기관: Yunwei H

2019년 2월 20일

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

교육 기관: Temuge B

2019년 4월 26일

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.

교육 기관: Serg D

2019년 10월 27일

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

교육 기관: Harold M

2018년 11월 25일

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.

교육 기관: Maxim

2019년 7월 5일

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.


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

교육 기관: Jakub B

2019년 6월 26일

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.

교육 기관: Arindam G

2018년 12월 20일

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

교육 기관: Antony J

2021년 6월 8일

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.

교육 기관: Jun W

2018년 11월 10일

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

교육 기관: Ben

2021년 1월 11일

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.

교육 기관: Prajwol L

2020년 5월 11일

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.

교육 기관: Navid K

2020년 1월 1일

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

교육 기관: Carlos V

2019년 2월 3일

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.

교육 기관: PLN R

2019년 8월 11일

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!

교육 기관: Nebojsa D

2020년 2월 29일

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

Otherwise course is excellent and was helpful for me

교육 기관: Ayman S

2019년 8월 17일

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.

교육 기관: zios s

2019년 12월 16일

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

교육 기관: Youdinghuan C

2020년 7월 14일

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

교육 기관: Md. A A M

2020년 7월 19일

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

교육 기관: 林佳佑

2018년 11월 2일

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

교육 기관: Mark D

2019년 2월 2일

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

교육 기관: Armando F

2019년 5월 31일

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

교육 기관: Mahmmoud M

2020년 3월 26일

A Very powerful course

Thanks for all google team

교육 기관: Enrique A M

2020년 10월 26일

Mil Gracias Google, Mil Gracias Coursera.