An application made from Flask that connects a machine learning model for the Iris toy dataset to a web interface.
IFPaaS - Iris Flower Prediction as a Service. An implementation of a machine learning microservice and its deployment to the cloud using: Python, Flask, Sklearn, Docker, CloudFormation, ECS, Fargate, Pytest, Travis CI, RESTPlus and Gunicorn.
The following code uses 5 different machine learning algorithm on the Iris dataset to predict the species of the flower
Implementation of K-Means clustering algorithm in python
Implementation of some machine learning algorithms for classification on the iris flowers data set
Iris flower classification among setosa, verginica and versicolor.
Higher Diploma in Science in Computing (Data Analytics) - Programme Module: Programming and Scripting (COMP08049)
A Django web application that predicts the species of an Iris flower based on its measurements, using a trained Random Forest model.
This Model/WebApp is going to classify the iris flowers for us using Artificial Neural Networks (ANN).
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