Workshop: Random Forests with scikit-learn
Introduction to Random Forests A random forest is an ensemble learning algorithm that combines many decision trees to produce a more accurate and stable model than any single tree alone. It belongs…
Workshop: Decision Trees with scikit-learn — Step-by-Step Tutorial
Introduction to Decision Trees A decision tree is a supervised machine learning algorithm that learns to make predictions by repeatedly splitting data into smaller groups based on feature values. The result is…
Workshop: Introduction to Neural Networks
This tutorial walks you through exactly how to create a neural network, line by line. We’ll start from zero and build the script incrementally so you understand why each part…
Implement Polynomial Regression in Python
Here's a very simple tutorial on how to do Polynomial Regression using Python and scikit-learn. Polynomial Regression is useful when your data has a curved relationship (not a straight line).…
Evaluating Linear Regression with Shapley Values, R² Score and VIF values
Linear Regression is one of the simplest and most fundamental supervised machine learning algorithms. It tries to predict a continuous numerical value (the target) by finding the best straight-line relationship…