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Dimensionality reduction, or dimension reduction, is the transformation of data from a high-dimensional space into a low-dimensional space so that the low-dimensional representation retains some meaningful properties of the original data, ideally close to its intrinsic dimension. Working in high-dimensional spaces can...

What is Normalization?# Feature Scaling is an essential step prior to modeling while solving prediction problems in Data Science. Machine Learning algorithms work well with the data that belongs to a smaller and standard scale. This is when Normalization comes into picture. Normalization techniques enables us to reduce...

Why do we need to impute missing data values?# Before going ahead with imputation, let us understand what is a missing value. So, a missing value is the part of the dataset that seems missing or is a null value, maybe due to some missing data during research or data collection. Having a missing value in a machine...