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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

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27 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...



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.


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