Time Series and Machine learning Approach for Weather Prediction by Suraj JagtapTime Series and Machine learning Approach for Weather Prediction by Suraj Jagtap
Time Series and Machine learning Approach for Weather Prediction
• Analyzed seasonal patterns in weather data, identifying maximum temperature peaks in April and May and minimum temperatures in December and January.
• Developed and evaluated SARIMA, Exponential Smoothing, and ARIMA models, determining Exponential Smoothing as the most effective with 94.4% accuracy.
Like this project
Posted Jul 3, 2024
I analyzed seasonal weather patterns, finding peak temperatures in April-May and lows in Dec- Jan. Exponential Smoothing model Forecast temp 94.4% accurately.