This is done by using Linear Regression Algorithm
Key features of it are :
Data Preparation: It reads weather data from a CSV file and explored its statistical properties.
Exploratory Data Analysis (EDA): It visualized the relationship between minimum and maximum temperatures using scatter plots and distribution plots.
Model Training: It splits the dataset into training and testing sets, trained a Linear Regression model on the training set, and retrieved the intercept and coefficients of the model.
Predictions: It uses the trained model to make predictions on the test set and compared these predictions to actual values.
Evaluation: I tevaluates the model's performance using various error metrics like Mean Absolute Error (MAE), Mean Squared Error (MSE), and Root Mean Squared Error (RMSE).