Scikit-learn Flashcards

A popular Python library for machine learning, offering simple and efficient tools for data mining and analysis.

Supports classification, regression, clustering, dimensionality reduction, and model selection algorithms.

Primarily uses NumPy arrays, Pandas DataFrames, and SciPy sparse matrices for input and output.

Scikit-learn is ideal for traditional ML algorithms; TensorFlow is better for deep learning and neural networks.

A feature to chain preprocessing and modeling steps into a single workflow object, enabling cleaner code and cross-validation.

A model evaluation method where data is split into multiple train/test sets to test robustness and avoid overfitting.

Any object in scikit-learn that implements the fit() and predict() methods (like classifiers, regressors, etc.).

Converts categorical values into numeric values using scikit-learn’s LabelEncoder.

A preprocessing technique to scale features by removing the mean and scaling to unit variance.

Yes! Scikit-learn is free and open-source, under the BSD license, and widely supported by the community.