Understanding Train-Test Split with a Simple London Real Estate Machine Learning Project

📰 Medium · Data Science

Learn to apply train-test split in machine learning using a simple London real estate project to improve model evaluation and avoid overfitting

beginner Published 12 May 2026

Action Steps

Load a London real estate dataset using Python and pandas
Split the data into training and testing sets using Scikit-learn's train_test_split function
Train a simple machine learning model on the training set
Evaluate the model's performance on the testing set
Compare the model's performance on the training and testing sets to detect overfitting

Who Needs to Know This

Data scientists and machine learning engineers can benefit from understanding train-test split to ensure reliable model performance and generalization

Key Insight

💡 Train-test split helps prevent overfitting by evaluating model performance on unseen data