fahmi551/Tanzania-Tourism--prediction-ML-Project

Machine learning project that predicts tourist preferences and booking behavior in Tanzania using data analysis and supervised learning models. # Tanzania Tourism Prediction using Machine Learning ## 📌 Project Overview This project focuses on predicting tourist preferences and booking behavior in Tanzania using Machine Learning techniques. The objective is to analyze tourism-related data and build predictive models that can help improve tourism planning and decision-making. ## 🎯 Problem Statement Tourism is a major economic sector in Tanzania. By analyzing historical tourism data, this project aims to predict patterns such as tourist interests, travel preferences, or booking behavior using data-driven methods. ## 🛠 Technologies Used - Python - NumPy - Pandas - Matplotlib - Seaborn - Scikit-learn ## 📊 Machine Learning Workflow 1. Data loading and exploration 2. Data cleaning and preprocessing 3. Feature encoding and selection 4. Model training 5. Model evaluation and performance analysis ## 🤖 Models Used The project applies supervised machine learning algorithms to build predictive models. Model performance is evaluated using appropriate metrics to ensure reliability. ## 📁 Project Files - `tanzania-tourism-prediction.ipynb` – Jupyter Notebook containing the full data analysis and model training process - `requirements.txt` – Python libraries required to run the project - `.gitignore` – Specifies files ignored by Git ## 🚀 How to Run the Project 1. Install the required libraries: ```bash pip install -r requirements.txt