Predict Air Quality with Machine Learning Comprehensive documentation for building machine learning systems that forecast Air Quality Index values. Learn about architectures, implementation patterns, and best practices.
Quick Start Get up and running with AQI Predictor in minutes.
Install the package
Install AQI Predictor using pip: pip install aqi-predictor
Configure your API key
Set up authentication by configuring your API credentials: from aqi_predictor import AQIClient client = AQIClient( api_key = "your_api_key_here" )
Get your API key from the dashboard after creating an account.
Make your first prediction
Submit environmental data to get an AQI prediction: prediction = client.predict({ "temperature" : 25.5 , "humidity" : 65 , "pm25" : 12.3 , "pm10" : 22.1 , "no2" : 15.2 , "location" : { "lat" : 37.7749 , "lon" : - 122.4194 } }) print ( f "Predicted AQI: { prediction.aqi } " ) print ( f "Category: { prediction.category } " )
{ "aqi" : 42 , "category" : "Good" , "confidence" : 0.94 , "timestamp" : "2024-03-15T10:00:00Z" , "components" : { "pm25" : 12.3 , "pm10" : 22.1 , "no2" : 15.2 } }
Explore by Topic Learn about core concepts and start building with AQI Predictor.
Core Concepts Understand the fundamentals of AQI prediction and our ML architecture.
Training Guide Train custom models on your own environmental datasets.
API Reference Complete API documentation for predictions and model management.
Data Sources Learn about supported data sources and environmental parameters.
Deployment Deploy AQI Predictor models to production environments.
Monitoring Track model performance and prediction accuracy over time.
Key Features Everything you need to build accurate air quality predictions.
Pre-trained Models Use production-ready ML models trained on extensive environmental datasets for instant predictions.
Multiple Data Sources Integrate environmental data from various sensors and APIs for comprehensive AQI analysis.
Real-time & Batch Get instant predictions via REST API or process large datasets with batch prediction endpoints.
Model Customization Train and fine-tune models on your specific regional data for improved accuracy.
Ready to Get Started? Start building accurate air quality predictions in minutes with our comprehensive API and ML tools.