Beginning Anomaly Detection Using



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Beginning Anomaly Detection Using Python-Based Deep Learning

 Examples of Time Series

 art_daily_no_noise

This data set has no noise or anomalies and is a normal time series dataset. As you can 

see below, the time series has values at different timestamps.

Dataset: art_daily_no_noise.csv

Figure 

6-39


 shows the code to generate a graph showing the time series.

Figure 6-39.  A graph showing the time series

Chapter 6   Long Short-term memory modeLS 




244

Using visualization, you can plot the new time series now. As shown below, the time 

series shows the datatime vs. the value column. Since there are no anomalies, everything 

is green. Figure 

6-40

 shows code to generate a graph showing anomalies.



Since this data set has no noise or anomalies and is a normal time series dataset, 

there are no anomalies (datapoints in RED) shown and everything is green.

Next, let’s examine another dataset which is different from the current dataset. You 

will build a LSTM model and see if there are anomalies or not.




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