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Data-Preprocessing

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In this project, I have explained some of the Data Preprocessing methods in a Jupyter Notebook. For the sake of easy understanding and to simplify the concepts, I have used a small sample dataset. In the real-world problem, the dataset will be more complex and huge.

I have covered the following topics in this project:

  • Handling Missing Data
  • Encoding Categorical Data
  • Splitting Dataset
  • Feature Scaling

To see the project, simply open the Jupyter Notebook: "Data Preprocessing.ipynb"

P.S. I will continue to update this folder with further Data Preprocessing methods.

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Data preprocessing methods explained with sample dataset

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