scikit-learn is widely used for which of the following tasks?

Scikit-learn is a popular Python library that specializes in machine learning tasks, particularly classification and regression. It provides various algorithms and tools for building predictive models based on available data. Classification refers to the task of predicting categorical outcomes, while regression involves predicting continuous outcomes.

The library includes numerous implementations of standard algorithms, such as decision trees, support vector machines, and linear regression, making it versatile for a wide range of supervised learning problems. Additionally, scikit-learn offers utilities for model evaluation, parameter tuning, and preprocessing data, all of which are critical components for building effective models in classification and regression tasks.

In contrast, tasks like real-time data streaming, game development, and cryptocurrency mining do not align with the primary functionalities of scikit-learn. Real-time data streaming typically involves frameworks built for processing large streams of data efficiently, while game development encompasses a broader set of skills and tools related to graphics, user interaction, and game physics. Cryptocurrency mining involves computational tasks more suited for specialized hardware and software focused on cryptographic calculations rather than on machine learning algorithms.