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Scikit-learn

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Scikit-learn is an open-source machine learning library that provides tools for supervised and unsupervised learning, model fitting, data preprocessing, model selection, model evaluation, and many other utilities.

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  • 💻 Scikit-learn is a Python library for machine learning that provides efficient data structures and algorithms for working with large datasets that cannot be handled by traditional statistical methods.
  • 📊 Scikit-learn offers a wide range of preprocessing techniques for handling data before training a model, including data scaling, normalization, handling missing values, and encoding categorical variables.
  • 📝 Scikit-learn provides feature extraction methods, such as Principal Component Analysis (PCA) and feature selection algorithms, allowing users to extract relevant features from high-dimensional data.
  • 🤖 Scikit-learn provides a wide range of machine learning algorithms for classification, regression, clustering, dimensionality reduction, and model selection. It also includes tools for data preprocessing, feature engineering, and model evaluation and selection.
  • 📈 Scikit-learn is widely used in the industry for classification, predictive analytics, and many other machine learning tasks. It is used by companies such as JPMorgan, Solido, and Otto Group, among others.
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