Introducing Scikit
scikit-learn
, which is commonly called Sklearn, is a very popular open source package in Python that is widely used for ML-related tasks, starting from data preprocessing, model training and evaluation, model selection, hyperparameter tuning, and more. One of the main selling points of the sklearn
package is the consistency of its interface across many implemented classes.
For example, all of the implemented ML models, or estimators, in sklearn
have the same fit()
and predict()
methods for fitting the model on the training data and evaluating the fitted model on the test data, respectively. When working with data preprocessors, or transformers, in sklearn
, the typical method that every preprocessor has is the fit()
, transform()
, and fit_transform()
methods for fitting the preprocessor, transforming new data with the fitted preprocessor, and fitting and directly transforming the data that is used to fit the preprocessor, respectively.
In Chapter 1, Evaluating...