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cases and goals differ from one project to another, and the available data problems also differ with it, and many obstacles and problems appear that can be solved through your preprocessing skills. Usually, this is the most important and longest step in the Lerning machine project construction steps, which strictly controls the accuracy and efficiency of your model.

ِِAs shown above, each step represents a clear and impressive change in the data. And you can work on each step with more than one algorithm and more than one method - at a time that requires you to focus on the quality and cost of the algorithms used.

During my studies in data science and working on machine learning projects i decided to made this NootBook which contains best preprocessing practice using Scikit-learn library with Python 3.8.3

You can use it as ## A reference and guide for projects to know the PreProcessing best practise

references sklearn.preprocessing