rkomitova/Tourism-Expenditure-Tanzania

# Tanzania Tourism Prediction: ML Project The main goal of this project was about to create a ML model to predict how much money a tourist will spend when visiting Tanzania. The data used for this can be found here. **Hypothesis:** Tourists are likely to spent more money depending on their age. To impove our hypothesis we trained a regression model to predict the total cost a tourist can spend. Contribution features are: - In what age group is a tourist - The country a tourist coming from - Which packages a tourist have - Number of tourists ### Exploratory Data Analysis (EDA) ### Data Cleaning and Feature Engineering ### Model Building and Evaluation --- # Requirements and Environment Requirements: - pyenv with Python: 3.9.8 Environment: 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 example_files/train.py ``` In order to test that predict works on a test set you created run: ```bash python example_files/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.