gabrielleuzinger/Algerian-Forest-Fires

The objective of the notebook is to create a model to classify the instances into fire or not fire This repository contains a **Model to to classify the instances into fire or not fire in the Algerian forests** based on the dataset available at the UC Irvine Machine Learning Repository. The objective of the notebook is to create a model to predict the number of comments in a blog post in the upcoming 24 hours. This project was set up following the premises of Reproducible Research, so that anyone can achieve the same results as me using the steps I followed in Jupyter Notebook. # Project libraries All dependencies can be found in the file `requirements.txt`, but are also listed below: * Numpy * Scikit-Learn * Pandas * Jupyter Notebook * Matplotlib To install the dependencies run in the project's main folder : `pip install -r requirements.txt`. To access the Jupyter Notebook that I created, run in the root folder of the `jupyter notebook` project. Soon after, your browser will open and just select the file `Algerian Forest Fires DataSet.ipynb`. # Project structure ```{sh} . |-report | |- markdown | | |- Algerian Forest Fires DataSet.md |-data |- Algerian Forest Fires DataSet.ipynb |- requirements.txt ``` The folder `report` contains a md file with a version of the report generated from the study done on that project. This file contains **all the insights and studies that were done, as well as a detailed description of how the project was developed**. **All references used to create this project are described in the report**.