INTRODUCING SCIKIT-LEARN

 

Scikit-learn is the core library for general machine learning. It offers an extensive repository of shallow algorithms¹ including logistic regression, decision trees, linear regression, gradient boosting, etc., a broad range of evaluation metrics such as mean absolute error, as well as data partition methods including split validation and cross validation.

Scikit-learn is also used to perform a number of important machine learning tasks including training the model and using the trained model to predict the test data.

The following table is a brief overview of common terms and functions used in machine learning from Scikit-learn.

 

Table 1: Overview of key Scikit-learn terms and functions