Easy Guide To Data Preprocessing In Python - KDnuggets

Machine Learning is 80% preprocessing and 20% model making. You must have heard this phrase if you have ever encountered a senior Kaggle data scientist or machine learning engineer. The fact is that this is a true phrase. In a real-world data science project, data preprocessing is one of the most important things, and it is one of the common factors of success of a model, i.e., if there is correct data preprocessing and feature engineering, that model is more likely to produce noticeably better results as compared to a model for which data is not well preprocessed. There are 4 main important steps for the preprocessing of data.