This is the Second task of the Sparks Foundation i.e. Implementing Unsupervised Learning On the Iris Dataset.

1. Task Description : This repository contains the solution for the second task of the Sparks Foundation's Data Science and Business Analytics internship program. The task involves implementing an unsupervised machine learning technique, focusing on clustering, dimensionality reduction, or anomaly detection.
2. Task Name: Unsupervised Machine Learning Technique
3. Task Number: 2
4. Task Objective: To implement an unsupervised machine learning technique to solve a specific problem, such as grouping similar data points or identifying outliers.
5. Dataset: The dataset for this task contains various features that are used to train and test the unsupervised machine learning model i.e. Iris.csv.
6. Files- Data Science And Business Analytics - Sparks Foundation Task - 02 Unsupervised machione learning: This ipynb file contains the code implemented for unsupervised learning, including various features for clustering, dimensionality reduction, or anomaly detection.
7. Data Science And Business Analytics - Sparks Foundation Task - 02 Unsupervised machione learning.ipynb: This Jupyter Notebook contains the Python code for implementing an unsupervised machine learning technique, such as KNN.
8. README.md: This file provides an overview of the repository and instructions for running the code.