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chris-hedemann/ml-project-air-pollution

Domaine:

environment and energy

Type de record:

project
Créateur:
chr
Hôte:
Machine Learning Project on Air Pollution in African Cities # ML project This is a notebook on our ML project for predicting air pollution in African cities. We are still cleaning things up, please come back in a week or so :-) 27.4.2023 Topic: Prediction PM10 concentrations based on weather conditions in African cities. Team: Christopher Hedemann, Stephen Kelly, Sarah Wiesner Bootcamp: neuefische Data Science 01/2023 ## Contents This repository contains the Jupyter notebook ML project as its main item. In this notebook, all the data work, including cleaning, analysis, modelling and visualization is collected. Furthermore, you can find the presentation given within the neuefische DS bootcamp. ## Requirements and Setup - pyenv - python==3.9.8 This repo contains a requirements.txt file with a list of all the packages and dependencies you will need. For installing the virtual environment you can either use the Makefile and run `make setup` or install it manually with the following commands: ```Bash pyenv local 3.9.8 python -m venv .venv source .venv/bin/activate pip install --upgrade pip pip install -r requirements.txt ``` ## Usage In order to train the model and store test data in the data folder and the model in models run: ```bash #activate env source .venv/bin/activate python data/train.py ``` In order to test that predict works on a test set you created run: ```bash python data/predict.py models/linear_regression_model.sav data/X_test.csv data/y_test.csv ``` ## Limitations Development libraries are part of the production environment, normally these would be separate as the production code should be as slim as possible.

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