Machine Learning — Getting Data Into Right Shape by Andrejus Baranovskis

When you build machine learning model, first start with the data — make sure input data is prepared well and it represents true state of what you want machine learning model to learn. Data preparation task takes time, but don’t hurry — quality data is a key for machine learning success. In this post I will go through essential steps required to bring data into right shape to feed it into machine learning algorithm.

Sample dataset and Python notebook for this post can be downloaded from my GitHub repo.

Each row from dataset represents invoice which was sent to customer. Original dataset extracted from ERP system comes with five columns:

customer — customer ID

invoice_date — date when invoice was created

payment_due_date — expected invoice payment date

payment_date — actual invoice payment date

grand_total — invoice total

Read the complete article here.

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