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Feature engineering is a machine learning technique that leverages data to create new variables that aren’t in the training set.
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It can produce new features for both supervised and unsupervised learning, with the goal of simplifying and speeding up data transformations while also enhancing model accuracy.
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Feature engineering is required when working with machine learning models.
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Regardless of the data or architecture, a terrible feature will have a direct impact on your model.
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Feature Engineering is a very important step in machine learning.
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Feature engineering refers to the process of designing artificial features into an algorithm.
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These artificial features are then used by that algorithm in order to improve its performance.
Here is a list of Jupyter Notebooks included in this repository :
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You can clone this repository using the following command:
git clone https://github.com/TheMrityunjayPathak/FeatureEngineering.git
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Install the Jupyter Notebook :
pip install notebook
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Launch the Jupyter Notebook :
jupyter notebook
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Open the desired notebook from the repository in your Jupyter environment and start learning!
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Contributions are Welcome!
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If you'd like to contribute to this repository, feel free to submit a pull request.
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This repository is licensed under the MIT License.
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You are free to use, modify and distribute the code in this repository.
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