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Are outliers ruining your machine learning predictions? Search for an optimal solution | by Kaushik Choudhury | Aug, 2020

Step 5- We will check if there are any null values in the training data and take any action required before going anywhere near modelling.

Here we can see that there are total 200,000 records in the training data and all three features have few values missing. For example, feature 1 has 60 values (200000 –199940) missing.