Iris Prediction System using MongoDB Atlas

Introduction

This project are meant to explore the uses of mongoDB atlas and how to connect it to a python application, while also utilize the benefits of virtual environment on python. The project is a simple machine learning model that predicts the species of iris flowers based on the length and width of the petals and sepals. The model is trained on the iris dataset which is a popular dataset for beginner machine learning projects. The dataset contains 150 samples of iris flowers and their corresponding species. The model is trained using the K-Nearest Neighbors algorithm which is a simple and easy to understand algorithm.

Getting Started!

• Clone the repository
• Install the required packages using the following command

pip install -r requirements.txt

• Create a .env file in the root directory and add the following environment variables

MONGO_URI = "your_mongo_uri"

Source

• Project Structure Inspiration: dev.to
• Iris Dataset: UCI Machine Learning Repository
• MongoDB Atlas: MongoDB
• K-Nearest Neighbors: Wikipedia
• Image Source: Unsplash