Predict Air Quality with Machine Learning: A Coding Tutorial

The video tutorial covers the impact of industrial activities on air quality, highlighting pollutants like ozone and carbon monoxide. It explains how poor air quality affects health and introduces the Air Quality Index (AQI). The tutorial then shifts to predicting AQI using machine learning, specifically LSTM models. It provides a step-by-step guide on downloading data from the EPA, preparing it in Google Sheets, and using Python in Google Colab to train and evaluate models for AQI prediction.

What steps are involved in gathering air quality data for prediction?

How do you preprocess the data for the LSTM model?

What is the importance of splitting the dataset into training, validation, and test sets?

What metrics should be recorded when training a model to predict AQI?