Download data
-> Go to https://www.ncdc.noaa.gov/cdo-web/search
-> Enter the years you want data for (I recommend starting with 1975), and search for the closest airport to you
-> Click add to cart on the airport you want
-> If there is no airport near you, try your city or country name instead
-> Go to the cart at https://www.ncdc.noaa.gov/cdo-web/cart
-> Select the csv format and click continue
-> Select all of the checkboxes for data types
-> Enter your email and click continue
-> You'll get an email with a link to download the data
Here are the steps involved in building the model:
-> Download weather data: The first step involves downloading weather data from NOAA. The link is provided above where you can download weather data for your area.
-> Clean the data: After downloading the data, you will need to clean it. This involves removing columns with missing values and ensuring the data is in a format suitable for machine learning models.
-> Train the model: Once the data is cleaned, you can use it to train a machine learning model. We used Ridge Regression, but you can also explore other models like XGBoost or Random Forest.
-> Evaluate the model: Finally, we evaluate the performance of the model. Mean Absolute Error is one of the metrics used to measure the accuracy of the model.