This project is to develop an anomaly detection model using Recurrent neural net on time series data. The data is from blood analyzer machine and the goal is to predict anomalous conditions of the machines before it goes wrong. Data is transformed and processed using spark sql. Prediction model is then developed based on the data and deployed to run in a real time streaming environment. The visualization chart for real time monitoring is developed using Bokeh library.
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Real time anomaly detection with RNN