An Introduction to Iris Dataset

The Iris flower data set or Fisher’s Iris data set is a multivariate data set introduced by the British statistician, eugenicist, and biologist Ronald Fisher in his 1936 paper the use of multiple measurements in taxonomic problems as an example of linear discriminant analysis.

Motivation

This project was started as a motivation for learning Machine Learning Algorithms and to learn the different data preprocessing techniques such as Exploratory Data Analysis, Feature Engineering, Feature Selection, Feature Scaling and finally to build a machine learning model.

In this project we will classify the Iris species based on their features such as Sepal length, Sepal width, Petal length and Petal width.

Iris Flower

In this Iris dataset, there are three kind of species i.e., Setosa, Versicolorand **Virginica **and 50 samples on each species having their respective Sepal Length, Sepal Width, Petal Length and Petal Width.

Table of contents

1. Data Collection
2. Data Pre-processing
3. Explorative Data Analysis (EDA)
4. Feature Observation
5. Feature Selection
6. Building Machine Learning Model
7. Model Performance
8. Predictions

#machine-learning