Data Preprocessing Steps for Machine Learning | Besant Technologies
In this video, I will try to simplify the exercise of data preprocessing, or in other words, the rituals programmers usually follow before it is ready to be used for machine learning models into 6 simple steps.
Step 1: Import Libraries
Step 2: Import the Dataset
Step 3: Taking care of Missing Data in Dataset
Step 4: Encoding categorical data
Step 5: Splitting the Dataset into a Training set and Test Set
Step 6: Feature Scaling
These are the general 6 steps of preprocessing the data before using it for machine learning. Depending on the condition of your dataset, you may or may not have to go through all these steps.
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