Repository for the EcoTech project at the GFG Hackathon, focusing on PM2.5 prediction using data analysis and machine learning models. Utilizes Jupyter Notebook, HTML, and Python for data visualization and model evaluation.
From the README
EcoTech GFG Hackathon PM2.5 Prediction Data Analysis of PM2.5 levels over time and the performance of machine learning models for predicting PM2.5 levels. Data Visualization The following images are the distributions of PM2.5 over a time-period. Machine Learning Models The following machine learning models were used for prediction: • AutoRegressive Model • Explainable Boosting Model • Random forest • MLP Regressor The performance of each model was evaluated using the root mean squared error (RMSE) and mean absolute error (MSE). Analysis of the ML Models From the analysis Neural Networks seems to be the best performing model. The Autoregressive model, as a benchmark, shows poor...
Skills
- Jupyter Notebook
- HTML
- Python
