Scikit-learn is a Python library for machine learning. It is a tool that allows you to easily implement machine learning algorithms such as regression, classification, agrouping, model evaluation and more.
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Machine learning is a subset of artificial intelligence. It focuses on teaching computers how to learn from data. Scikit-learn is a library that allows us to perform classification, regression and clustering algorithms in Python.
What is Scikit-learn?
Scikit-learn also known by the name sklearn, it is an open source machine learning library for the Python programming language. It includes various classification, regression and clustering algorithms. It also provides various tools for model adjustment, data preprocessing, model selection, model evaluation and many other tools. The library provides dozens of built-in machine learning algorithms and models, called estimators. Each estimator can be fitted to certain data using its adjustment method. The fitting method takes two inputs:
A sample matrix X - a sample X usually consists of a sample and a function. Samples are represented as rows and functions as columns.
Target value Y - these are real numbers for regression tasks or whole numbers for classification. For unsupervised learning tasks, y need not be specified.
Scikit-leran requires the installation of the numpy and scipy libraries. If you have already installed both libraries, use the command below to install Scikit-learn.
pip install -U scikit-learn