https://github.com/grindelfp/iris-ml

A basic machine learning project, aimed to study the machine learning concepts and apply them to a real worls Iris dataset.
https://github.com/grindelfp/iris-ml

ipynb iris-classification iris-dataset machine-learning

Last synced: about 2 months ago
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A basic machine learning project, aimed to study the machine learning concepts and apply them to a real worls Iris dataset.

• Host: GitHub
• URL: https://github.com/grindelfp/iris-ml
• Owner: GrindelfP
• License: mit
• Created: 2023-11-14T06:48:25.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2023-11-19T18:04:40.000Z (about 1 year ago)
• Last Synced: 2024-11-13T08:41:03.479Z (about 2 months ago)
• Topics: ipynb, iris-classification, iris-dataset, machine-learning
• Language: Jupyter Notebook
• Homepage:
• Size: 73.2 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.adoc
  • License: LICENSE

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README

        
= Iris Machine Learning =

== Description ==

This is a machine learning project that uses the Iris dataset to predict the species of a flower based on the length and width of the petals and sepals.

The aim of the project is to study the basic concepts of machine learning and to apply them to a real world dataset.

== The task ==

The task is to predict the species of a flower based on the length and width of the petals and sepals.

== The workflow ==

1. Import the dataset and turn it into a dataframe

2. Explore the dataset

3. Append the species column to the dataframe

4. Plot the data to visualise it and spot the possible clusters

5. Split the data into training and testing sets

6. Train the model

7. Test the model

8. Output the results