K-means Using Pyspark

Prerequisite :

• You must have python 3.7 or more installed on your system.

• You must have hadoop and pyspark installed on your system

• You must have a Spyder, Jupyter notebook on your system. Spyder or jupyter notebook come up with anaconda. you just need to launch them after installing anaconda.

• If you work on a google colab no need to install python or Any other IDE, you just need to sign in with google colab and install pyspark using “!pip install pyspark” this command.

Skilled required:

• Python programming language

• Basic Statistical analysis skills

• Machine learning concept

What you’ll learn

• How to read the data using pyspark dataframe

• Perform Basic Exploratory Data analysis using pyspark

• How to calculate the silhouette score

• How to create cluster by apply k-means algorithm using pyspark

Problem Statement or Description:

This project will show how to create a cluster of data by applying k-means algorithms using pyspark on animal milk dataset. In this project, create a cluster of animals based on their milk features like how much protein, fat, lactose, ash, water contains in their milk.

Key highlights of projects or Essence

• This project is about clustering analysis.

• This project shows you how to read the data and perform some basic Exploratory data analysis using pyspark

• This project shows you how to perform data preprocessing.

• This project shows you how to create cluster of unlabeled data

Packages and module used :

• Pyspark

• VectorAssembler

• KMeans

• ClusteringEvaluator

• Matplotlib

• StandardScaler

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