Scikit-learn is a popular Python library for machine learning that provides simple and efficient tools for data mining and data analysis, offering a wide range of algorithms for classification, regression, clustering, and dimensionality reduction. Here, you will find hands-on tutorials, example projects and best practices for using Scikit-learn
Introduction In this tutorial, we want to scale features of a Pandas DataFrame. In order to do this, we use the StandardScaler() class and the MinMaxScaler() class of Scikit-Learn. Import Libraries First, we import the following python modules: import pandas as pd from sklearn.datasets import fetch_california_housing from...
Introduction In this tutorial, we want to split data into train and test sets. In order to do this, we use the train_test_split() function of Scikit-Learn. Import Libraries First, we import the following python modules: import pandas as pd from sklearn.model_selection import train_test_split Load...