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Hands-on with Feature Selection Techniques
Get to know the features selection techniques in a hands-on way, Throughout the series, weโll explore a range of different methods and techniques used to select the best set of features that will help you build a simpler, faster, and more reliable machine learning models.
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Getting Started Here are the set of articles:
- An Introduction
- Filter Methods
- Wrapper Methods
- Embedded Methods
- Hybrid Methods
- More Advanced Methods
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Prerequisites You should have the following librariesand softwares installed on your PC alongside with Python:
- Pandas
- Numpy
- Sklearn
- Matplotlib
- Jupyter notebook
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Contributing If you want to contribute to this project and make it better with new ideas, your pull request is very welcomed. If you find any issue just make an issue in the repository issue section, thanks a lot.
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License This project is licensed under the MIT License - see the LICENSE.md file for details