A simple Amazon Echo project to participate in the EMC Underground Challenge
The solution's goal is to predict whether a support case will be open for a specific EMC array. The prediction is based ML (Machine Learning) inside an AWS lambda function using an existing historical data set.
- Initialize ML NN (neural network)
- Load a training set for a specified frame
- Ask user for a date
- Support Predictor tells the chances for a new support request being open for a frame
- (User) "Alexa, use Support Predictor"
- (Alexa) "Welcome to the Dell EMC Support Predictor. I have data for two frames: 1234 and 5678. Please tell me which one to use?"
- (User) "Help!"
- (Alexa) "Please chose one of the ZZ frames for a prediction about an upcoming support request. You may also ask to list the frames."
- (User) "List frames please"
- (Alexa) "I have data for ZZ frames. And they are: 1234,2345,3456,4567. Please choose a frame."
- (User) "Frame 1234"
- (Alexa) "Building the neural network for frame 1234. Built successfully! Which day should I predict for?"
- (User) "Today" || "Tomorrow" || "A month from now" || "day after tomorrow"
- (Alexa) "There is a XX% chance that there is an issue on DATE!"
The project is using NODE.JS. The ML component is the "synaptic" library; also planning to use AWS S3 for the lists.
cd src && npm install synaptic aws-sdk