Weather Temperature Forecast using ML

This project builds a machine learning model that predicts future temperature based on historical weather data. The system analyzes past temperature records, humidity, wind speed, pressure, and other climate conditions to understand patterns and seasonal trends.

The workflow includes data cleaning, handling missing values, feature engineering, time-series preparation, model training using algorithms like Linear Regression, Random Forest, or LSTM, and model evaluation using MSE and MAE.

This helps provide accurate temperature forecasts that can be used for planning, agriculture, travel, and weather-based applications.