Weather prediction using python. Weather forecasting is the task of predicting the state of the atmosphere at a future time and a specified location. There are many types of machine learning algorithms to predict the weather, of which two most important algorithms in predicting the weather are Linear Regression and a variation of Functional Regression. These models are trained based on the historical data provided of any location. Input to these models are provided such as if predicting temperature, then minimum temperature, mean atmospheric pressure, maximum temperature, mean humidity, and classification for 2 days.
1.Open the terminal (Ctrl + Alt + T).
2.Navigate to the folder where your .ipynb file saved.
3.Type jupyter notebook
4.Open the file that you want to read.
5.To run the program line by line press shift+Enter.
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Import all the necessary libraries.
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dataSet = Read dataset
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Split dataSet into training and testing sets.
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Apply the linear regression to the set of data.
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Visualize the training Test Results.
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Plot the graph.