Stack Explorer

scikit-learn

machine-learning

Simple and efficient traditional machine learning library

10M/week → Stable

Features

classical-mlalgorithmspreprocessingsimple

Pros and Cons

Ventajas

  • + Consistent and easy-to-use API
  • + Wide collection of classical algorithms
  • + Excellent for learning ML
  • + Perfect integration with NumPy/Pandas
  • + Exemplary documentation

Desventajas

  • - No deep learning support
  • - No native GPU support
  • - Limited for big data
  • - Not for neural networks

Use Cases

  • Classification and regression
  • Clustering and dimensionality reduction
  • Data preprocessing
  • Model selection and validation
  • Traditional ML pipelines

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