Metadata-Version: 2.4
Name: iris-species-cli
Version: 1.0.1
Summary: A simple CLI iris species predictor model
Author: omar elhalaby
License-Expression: MIT
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pandas
Requires-Dist: scikit-learn
Dynamic: license-file

# Iris species predictor
simple GUI web model for predicting Iris species using mesurments
input DataType : float, example: 1.0 or 1 or 7.2 (dosen't accept commas ",")

# Libraries needed
Pandas, scikit-learn, flask, gunicorn

# Installing The Required Libraries
```shell
$ pip install pandas
$ pip install scikit-learn
$ pip install flask
```

# Dataset
the dataset contains 150 samples of 3 species of Iris flowers , perfectly balanced 50,50,50
the dataset dosent have any unrealistic measurments or missing values.

# Running the file

make sure the csv file and the python file are in the same directory and then open a terminal and type:                     
```shell
$ python app.py
```
will launch a local web server so you can try the app on a GUI
# iris-species-predictor-web
# iris-species-predictor-web
# iris-species-predictor-web
# iris-species-predictor-web
# iris-species-predictor-web
