July 2018
Beginner to intermediate
312 pages
8h 31m
English
Content preview from Hands-On Natural Language Processing with Python
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TensorBoard visualization
We will first look at the accuracy and loss during the training. Start TensorBoard, pointing to the log directory /tmp/tflearn_logs (default for tflearn):
We find that both the validation and training loss decrease with the time steps. Note that the validation set we used was the same as from training, which was just a quick hack. You can set aside a separate validation set from the original data like we did for the test set. Next, we will look at the graph of the model in TensorBoard, as shown in the following screenshot:
Graph of model in TensorBoard
As explained previously, we have an input layer that feeds the ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.