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![Teaching to Add
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The document discusses teaching recurrent neural networks (RNNs) using TensorFlow, covering theory and practical examples such as learning sine waves, addition, and handwriting. It highlights the architecture for implementing RNNs, including initializing RNN cells and defining hyperparameters. Additionally, it mentions the use of R and Shiny for creating a visual interface to interact with TensorFlow models.






























![Teaching to Add
(array([[7],
[4],
[1],
[8],
[0],
[3],
[1],
[5],
[6],
[9],
[2],
[0],
[0],
[0],
[0]]), 46.0)](https://image.slidesharecdn.com/tensorflow-160525121422/85/Teaching-Recurrent-Neural-Networks-using-Tensorflow-May-2016-31-320.jpg)





