A real time web application, that is built using the University of California, Irvine presented Iris Dataset, which basically predicts three types of Iris flowers based on the length, width of the sepals and the petals. There are three type of Iris flowers, that can be predicted: Iris Versicolor, Iris Setosa and Iris Virginica.Plesae ⭐ this repository if you found it useful.
Python
Numpy
Pandas
Matplotlib
Heroku for deploying our web application
Git for Version Control
Firstly Clone the Repository onto your local machine using the following command:
git clone https://github.com/lionelsamrat10/Iris-Flower-Prediction-Machine-Learning-Web-App.git
A good practice to start with a new project and use it, is to make a virtual enviornment for the particular project. Here is the steps for making virtual enviornment ::
pip install virtualenv
python -m virtualenv myenv
Run commands on python terminal or anaconda terimial or any terminal you are using in your system.
pip install -r requirements.txt
- Run
python app.py
. - The app will be up and running at the following URL
http://localhost:5000/
- Now provide the length and width of the sepal and petal of the flowers (Which can be found in the Iris.data file) and then submit the values and the app will predict the flower with almost 100% accuracy.
- The app is deployed using heroku: Click here
Hope you like this project !!!