Feature Engineering and Selection for Regression Models with Python and Scikit-learn
This guide provides tips on feature exploration, engineering, and selection for machine learning using Python and Scikit-Learn
Random Decision Forests
6 tutorials
Using Random Search to Tune the Hyperparameters of a Random Decision Forest with Python
Learn how to use Random Search to tune the model hyperparameters of a Random Forest with Python that predicts house sale prices.
How to Measure the Performance of a Machine Learning Classifier with Python and Scikit-Learn?
Using confusion matrix and error metrics for measuring classification performance in machine learning with Python.
Classifying Reported Crime Categories in San Francisco with Python
Build and evaluate a reproducible multiclass model for historical San Francisco incident categories, including responsible-use limitations.
Customer Churn Prediction - Understanding Models with Feature Permutation Importance using Python
This tutorial shows how to build a customer churn prediction model in telecommunications. We will use Python and measure feature importance.
Tuning Model Hyperparameters with Grid Search at the Example of Training a Random Forest Classifier in Python
Learn how to tune the model hyperparameters of a Random Forest that predicts the survival of Titanic passengers using grid search in Python.