Machine Learning Data Preprocessing | How to handle datasets

In this video, we will discuss the data preprocessing steps overview in machine learning tasks. There are five important checks we must address. We need to handle missing data in the dataset, categorical data handling in dataset, handling imbalance data, outlier handling in data, and feature scaling and transformation. Typically if we do not handle these noise in data, this can end up in less accuracy and higher convergence time.
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