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This repository contains a machine learning model built using regression techniques to predict forest fires. The model utilizes regression algorithms to analyze various environmental factors and their impact on the likelihood of a forest fire occurrence.

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Forest_Fire_Prevention

The forest fire is the burning of tropical, temperate and boreal forest either by natural fire or man-made fire and is related to land clearing and deforestation. Natural forest fire includes an unplanned burning of forest due to lightning, while human-induced forest fire results from the unauthorized burning practice of forests for attaining farmland. In spite of low commitment of boreal forest in worldwide biomass burning emission, there is 10-folds increase in the extent of boreal forest burning in recent year.

Forest fires prediction combines weather factors, terrain, dryness of flammable items, types of flammable items, and ignition sources to analyze and predict the combustion risks of flammable items in the forest. Forest fire prediction has developed rapidly in various countries in the world since its inception in the 1920s

Technology Stack used in this project

1. HTML

2. css

3. JavaScript

4. Materialize css

5. Sklearn, pandas

6. Flask

7. AWS EC2

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This repository contains a machine learning model built using regression techniques to predict forest fires. The model utilizes regression algorithms to analyze various environmental factors and their impact on the likelihood of a forest fire occurrence.

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