Find the association between milk composition and environmental conditions (weather station data, barn environmental data, and body temperature) and prediction of production shifts based on environmental data.
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Processes initial training data to combine features and labels for the ML model
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Listens for streams of inputted information from multiple farms at once
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Cleans data and eliminates outliers
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Segregates and stores data in a database
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Makes weekly predictions on the quality of milk based on the past week’s data
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Relays those predictions to the farmers
- Python script for filtering and combining the dairy data
- Spark code for filtering and combining our streamed data
- Multiple Node JS servers hosted on Azure VM’s behind an Azure load balance
- MongoDB Atlas cluster to store data
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Loads data from MongoDB Atlas into a dataframe
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Trains ML model based on given training data and valid MongoDB training data
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Executes ML model for last 7 days of cow/environmental data
brew install scala download intellij, open, go to configure, get scala plugin brew install sbt go to cloud/test3/test3 run sbt in the terminal in the shell, run "update" after that, in the shell, run "run" There should be a line in there that says TEXT FILE LENGTH: 4 scala 2.12.10