Iris Flower Classification is the "Hello World" of Machine Learning.
This project requires Python 2.7 and the following Python libraries installed:
Install Anaconda, a pre-packaged Python distribution that contains all of the necessary libraries and software for this project.
The dataset for this project originates from the UCI Machine Learning Repository. The Iris flower data set or Fisher's Iris data set is a multivariate data set introduced by the British statistician and biologist Ronald Fisher in his 1936 paper The use of multiple measurements in taxonomic problems as an example of linear discriminant analysis.
The data set consists of 150 samples from each of three species of Iris (Iris setosa, Iris virginica and Iris versicolor). Four features were measured from each sample (in centimetres):
- Length of the sepals
- Width of the sepals
- Length of the petals
- Width of the petals
Go to the Anaconda Prompt, change the directory to the project directory and run the command 'python api.py'. It should run commands as shown in the screenshot -
After that, open your browser and enter the address- 'http://localhost:8000'. It should open the following -
In the given fields, enter the required values -
And you have your precdiction !
