Project Topic
Flowers Classification Using Machine Learning
Project Features
The Iris Dataset contains four features (length and width of sepals and petals) of 50 samples of three species of Iris (Iris setosa, Iris virginica and Iris versicolor). These measures were used to create a linear discriminant model to classify the species.
Programming Languages Used
Python, Machine Learning
Framework/Libraries Used
1. Numpy- 1.19.3
2. Matplotlib- 3.3.2
3. Seaborn – 0.11.1
4. Pandas – 1.2.4
5. Scikit-learn – 0.24.2
Project Description
Classification of iris flowers is perhaps the best-known example of machine learning.
The aim is to classify iris flowers among three species (Setosa, Versicolor, or Virginica) from sepals’ and petals’ length and width measurements.
The iris data set contains fifty instances of each of the three species.
The central goal is to design a model that makes proper classifications for new flowers. In other words, one which exhibits good generalization.