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data-analysis

In machine learning, especially in data science, dealing with the data is so important that it can affect the best models in a bad way. In real life, we can't have pure data like no NaN values or extreme outliers etc. Before applying any algorithm to the data, first we should get to know our data. This repository is created to analyze and clean the data from A to Z.

Enjoy cleaning :)

ibrahm Halil Bayat Department of Electronics and Communication Engineering İstanbul Technical University İstanbul, Turkey

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Analyzing and visualizing the data, Binning categorical features. Detecting extreme outliers and removing outliers. ANOVA

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