Artificial Intelligence & Machine Learning

Scikit-learn

Definition

Scikit-learn is a free software machine learning library for the Python programming language. It features various classification, regression and clustering algorithms including support vector machines, random forests, gradient boosting, k-means and DBSCAN.

Why It Matters

Scikit-learn is the go-to library for classical (non-deep learning) machine learning in Python. It provides a simple, consistent, and powerful toolkit for nearly all standard ML tasks, from data preprocessing to model evaluation.

Contextual Example

A data analyst wants to build a simple model to predict customer churn. They would use scikit-learn to load the data, split it into training and testing sets, train a logistic regression or random forest model, and evaluate its performance, all within a few lines of Python code.

Common Misunderstandings

  • Scikit-learn is not designed for deep learning; for that, you would use a library like TensorFlow or PyTorch.
  • It has excellent documentation and a very consistent API, which has made it extremely popular.

Related Terms

Last Updated: December 17, 2025