Understanding the scikit-learn machine learning library

scikit-learn (https://scikit-learn.org/) is an open source machine learning library for Python. Initially released in 2007, it is one of the most popular machine learning libraries for solving many machine learning tasks, such as classification, regression, clustering, and dimensionality reduction.

scikit-learn is widely used by companies in different industries and academics for solving real-world business cases such as churn prediction, customer segmentation, recommendations, and fraud detection.

scikit-learn is built mainly on top of three foundational libraries: NumPy, SciPy, and matplotlib. NumPy is a Python-based library for managing large, multidimensional arrays and matrices, with additional mathematical functions to operate on the arrays and matrices. SciPy provides scientific computing functionality, such as optimization, linear algebra, and Fourier Transform. Matplotlib is used for plotting data for data visualization...