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学生对 Google 云端平台 提供的 Sequence Models for Time Series and Natural Language Processing 的评价和反馈

238 个评分
30 个审阅


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 COMPLETION CHALLENGE Complete any GCP specialization from November 5 - November 30, 2019 for an opportunity to receive a GCP t-shirt (while supplies last). Check Discussion Forums for details....



Aug 11, 2019

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!


Nov 11, 2018

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


26 - Sequence Models for Time Series and Natural Language Processing 的 30 个评论(共 30 个)

创建者 Silviu M

Aug 28, 2019

The content is amazing and some of the implementations are really awesome! I am not a programmer but this course opened me the eyes to see how many business opportunities are there to use data for AI, in new products and services

创建者 Bablesh S

Oct 18, 2019

Good Course with enough practical exercises to get some hands on experience.

创建者 Soroush A

Jul 30, 2019

lecturer talks too fast and not easy to understand. This topic was one of my favorites.

创建者 ssen-advanced

Nov 06, 2019

The chinese intonation and pronunciation was uncomfortable

创建者 Serg D

Oct 27, 2019

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