
To analyze the impact of education levels on house prices
To implement various machine learning algorithms to predict house prices based on education data
To evaluate the performance of different machine learning models in predicting house prices
Collect and preprocess data on house prices and education levels
Explore the relationship between education levels and house prices using data visualization techniques
Implement different machine learning algorithms such as linear regression, decision trees, and random forests
Evaluate the performance of each model using metrics like mean squared error and R-squared
Compare and contrast the results of different machine learning models
Write a report detailing the impact of education on house prices and the effectiveness of machine learning techniques in predicting house prices.