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Country Data Analysis Using Clustering

Data Science
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Prerequisite :

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

  • You must have Spyder, jupyter notebook or pycharm installed 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 Colab no need to install python or Any other IDE, you need to just sign in with google Colab.

What you’ll learn

  • How to read the data using pandas dataframe

  • Perform Basic Exploratory Data analysis

  • Determining the number of cluster using Elbow method

  • Determining the silhouette score

  • How to check outliers from the dataset using boxplot.

  • How to implement the various clustering techniques on dataset e.g K-means, DBSCAN, Hierarchy, Mean Shift clustering algorithm.

Problem Statement or Description:

The dataset contains health and socio economic related 10 columns and 167 records. The focus of this research is how to categorise the countries using socio-economic and health factors that determine the overall development of the country.

Key highlights of projects or Essence

  • This project is aboutClustering analysis.

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

  • This project show you how to find the number of cluster using elbow method

  • This project show you how to find silhouette coefficient or silhouette score

  • This project shows you how to implement the clustering algorithm on the dataset and how to visualize data.

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Data Science, Machine Learning, Deep Learning, scikit-learn, pandas, Clustering

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