Scikit-learn is an AI tool for machine learning in Python. It provides simple and efficient tools for predictive data analysis and is accessible to everyone, with reuse in various contexts. It is built on popular libraries like NumPy, SciPy, and matplotlib, and it is open source with a BSD license. The tool offers functionality for classification, regression, clustering, dimensionality reduction, model selection, and preprocessing. It includes algorithms such as gradient boosting, nearest neighbors, random forest, logistic regression, k-means, PCA, and feature selection. Applications of scikit-learn range from spam detection and image recognition to drug response and stock price prediction. It also helps with tasks like customer segmentation, visualization, and parameter tuning. Scikit-learn is well-regarded for its ease of use, performance, and variety of implemented algorithms, making it accessible to both beginners and advanced users in the field of machine learning.