Skip to content

πŸŒΌπŸŒ·πŸ’» A fully deployed predicting system to predict the species of Iris flower.

Notifications You must be signed in to change notification settings

Rakesh-Naidu/Iris-species-Prediction

Folders and files

NameName
Last commit message
Last commit date

Latest commit

Β 

History

19 Commits
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 

Repository files navigation

Iris-species-Prediction πŸŒΌπŸŒ·βœ”

Table of Contents

Demo

Link: https://irispredictionapi.herokuapp.com/

Overview

This is a Flask web app which predicts the median value of house.

Installation

The Code is written in Python 3.6.10. If you don't have Python installed you can find it here. If you are using a lower version of Python you can upgrade using the pip package, ensuring you have the latest version of pip. To install the required packages and libraries, run this command in the project directory after cloning the repository:

pip install -r requirements.txt

Deployement on Heroku

Login or signup in order to create virtual app. You can either connect your github profile or download ctl to manually deploy this project.

Our next step would be to follow the instruction given on Heroku Documentation to deploy a web app.

Directory Tree

β”œβ”€β”€ template
β”‚Β Β  β”œβ”€β”€ index.html
β”œβ”€β”€ Procfile
β”œβ”€β”€ README.md
β”œβ”€β”€ app.py
β”œβ”€β”€ Iris_EDA.ipynb
β”œβ”€β”€ Iris_Model.ipynb
β”œβ”€β”€ model.pkl
β”œβ”€β”€ housing.csv
β”œβ”€β”€ requirements.txt

Technologies Used

About

πŸŒΌπŸŒ·πŸ’» A fully deployed predicting system to predict the species of Iris flower.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages