- Did some light cleaning of the data on Apache Spark(pySpark).
- Uploaded the data to data bricks for distributed computing on the dataset.
- Did feature engineering on the dataset, transforming it to a form the model could train on.
- Trained the Linear regression model on the databricks cluster with 75% of the data.
- Made perdictions from the model.
- r2 was at 0.4
-
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Using Apache pySpark on DataBricks, I was able to do feature Engineering on Customer Data, trained and used a Linear Regression Model to predict their bill based on previous customer trends.
arnoldchrisoduor1/LinearRegression-Model-with-ApacheSpark-and-DataBricks
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Using Apache pySpark on DataBricks, I was able to do feature Engineering on Customer Data, trained and used a Linear Regression Model to predict their bill based on previous customer trends.
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