Iris flowers Data Classification using Python Machine Learning

Iris flowers dataset is one of the best dataset in classification literature. The classification of iris flowers machine learning project is often referred to as the basic program of machine learning.

Using:

  • google colab
  • numpy
  • pandas
  • scikit-learn

Dataset description

From the UCI Machine Learning Repository.

Features:

  • sepal length (cm)
  • sepal width (cm)
  • petal length (cm)
  • petal width (cm)
  • species (Iris-setosa, Iris-versicolor, Iris-virginica)

#On this project are testing a multiple regrassion model there example are below

  • DecisionTreeClassifier Model
  • KNeighborsClassifier Model
  • Logistic regression Model -Support vector machine Model

References

*https://medium.com/gft-engineering/start-to-learn-machine-learning-with-the-iris-flower-classification-challenge-4859a920e5e3
*https://www.neuraldesigner.com/learning/examples/iris-flowers-classification
*https://www.skyfilabs.com/project-ideas/iris-flower-classification-using-machine-learning
*https://analyticsindiamag.com/start-building-first-machine-learning-project-famous-dataset/
*https://www.youtube.com/watch?v=FLuqwQgSBDw&ab_channel=AppliedAICourse
*https://www.youtube.com/watch?v=CLvboTdwpjc&ab_channel=RealKnow
*https://youtu.be/Y17Y_8RK6pc?list=PL5tcWHG-UPH1OeZ2vU5xQd7RVpkWvwJny
*https://youtu.be/ACdBKML9l4s

The goal is to predict the species of a new sample of iris flower given its features.