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Iris flower classification in its three species based on their petal and sepal, width and length.

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Iris Classification Project

Hello everyone,

Welcome to the Iris Classification project – a beginner-friendly exploration into the world of machine learning, akin to the "Hello World" of programming. In this project, we aim to classify Iris flowers into three distinct species based on certain features.

What's This Project About?

The Iris Classification project is a classic example in the realm of machine learning, perfect for those stepping into the exciting world of data science. Using a dataset that includes measurements of iris flowers, we've trained a model to predict the species to which each iris belongs.

Quick Overview

  1. Objective: Classify Iris flowers into three species.
  2. Dataset: Includes measurements like sepal length, sepal width, petal length, and petal width.
  3. Algorithm: We've used a simple yet effective classification algorithm.
  4. Results: Explore the accuracy and insights gained from the model.

Why Iris?

Iris classification is often considered the "Hello World" in the machine learning realm because of its simplicity and educational value. It provides a great starting point for understanding how machine learning algorithms work.

Feel free to delve into the project, check out the code, and understand the basics of classification. Questions and feedback are always appreciated!

Happy learning,

[ Anjali Singh]

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Iris flower classification in its three species based on their petal and sepal, width and length.

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