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Opiniones y comentarios de aprendices correspondientes a Sequence Models for Time Series and Natural Language Processing por parte de Google Cloud

4.5
142 calificaciones
16 revisiones

Acerca del Curso

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...

Principales revisiones

JW

Nov 11, 2018

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

MD

Feb 03, 2019

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

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1 - 18 de 18 revisiones para Sequence Models for Time Series and Natural Language Processing

por vincent p

Feb 24, 2019

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

Explanations of what we are doing are light.

por Yunwei H

Feb 20, 2019

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

por Harold L M M

Nov 25, 2018

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.

por Temuge B

Apr 26, 2019

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.

por Arindam G

Dec 20, 2018

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

por Jun W

Nov 11, 2018

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

por Marios N

Jun 10, 2019

Very helpful but needs more in depth detail how attention works, how encoder/decoder trains and makes predictions

por Armando F

Jun 01, 2019

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

por Nguyễn V L

Apr 14, 2019

pretty great

por Carlos V

Feb 03, 2019

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.

por Mark D

Feb 03, 2019

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

por ELINGUI P U

Jan 27, 2019

Great one!

por Raja R G

Dec 11, 2018

Good

por Elias P

Dec 04, 2018

I really loved it!

por Hemant D K

Dec 01, 2018

Very informative, very much useful to my ongoing work on NLP.

por Печатнов Ю

Nov 22, 2018

First quiz is very bad

But totally the course is interesting and I like it :)

por 林佳佑

Nov 02, 2018

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

por Jason C

Oct 19, 2018

Quite a challenging course so far.