medson10 / mlops_project

MLOps Final Project

Dataset used

https://www.kaggle.com/datasets/shree1992/housedata

Dataset description

The dataset contains information about houses in Sidney and Melbourne. It includes the information about the number of bedrooms, bathrooms, size, location, price and other features of the houses.

Requirements

This project can be run using Asdf and Poetry, or using only Python.

Installation

Using Asdf and Poetry

1. Install Asdf if you haven't already.
2. Clone the repository.
3. Run asdf install this will install the required versions of Python and Poetry.
4. Navigate to the project directory.
5. Run poetry install to install the dependencies.

Using only Python

1. Install Python if you haven't already.
2. Clone the repository.
3. Navigate to the project directory.
4. Run pip install -r requirements.txt to install the dependencies.

Getting Started

• Download the dataset from https://www.kaggle.com/datasets/shree1992/housedata
• Unzip the dataset and place it in the data directory with the name housing.csv
• If you are running with Poetry add poetry run before the command.
• Start the MLFlow server by running mlflow ui --backend-store-uri sqlite:///mlflow.db
• Run python main.py to train and register the models.
• Serve the model as an API by running mlflow models serve -m ./mlruns/1/<artifact_id>/artifacts/random_forest_model -p 8000 --no-conda
• Run python monitor.py to load a sample data, check for anomalies and generate a report.