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Sequence Models for Time Series and Natural Language Processing, Google Cloud

4.5
45 ratings
8 reviews

About this Course

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...
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8 Reviews

By Raja Ranjith Garikapati

Dec 11, 2018

Good

By Elias Papachristos

Dec 04, 2018

I really loved it!

By Hemant Devidas Kshirsagar

Dec 01, 2018

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

By Harold Lawrence Marzan Mercado

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.

By Печатнов Юрий

Nov 22, 2018

First quiz is very bad

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

By Jun Wang

Nov 11, 2018

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

By 林佳佑

Nov 02, 2018

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

By Jason Cheung

Oct 19, 2018

Quite a challenging course so far.