June 2019
Intermediate to advanced
308 pages
7h 21m
English
Content preview from Hands-On Deep Learning for IoT
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Use case one
We considered a three-LSTMs-layered network architecture for the CPU utilization based host/device-level intrusion detection. The following diagram presents the LSTM architecture we used:
We can train and test the model by running the lstm_anomaly_detection.py file (available in the chapter's code folder) as follows:
python lstm_anomaly_detection.py
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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.