https://github.com/raj-pulapakura/basketball-players-analysis

This repo features an analysis on various basketball players, using unsupervised learning techniques.
https://github.com/raj-pulapakura/basketball-players-analysis

basketball clustering coursera data-science exploratory-data-analysis machine-learning pca-analysis unsupervised-machine-learning

Last synced: 5 days ago
JSON representation

This repo features an analysis on various basketball players, using unsupervised learning techniques.

• Host: GitHub
• URL: https://github.com/raj-pulapakura/basketball-players-analysis
• Owner: raj-pulapakura
• Created: 2023-09-30T09:51:50.000Z (about 1 year ago)
• Default Branch: master
• Last Pushed: 2023-09-30T10:11:08.000Z (about 1 year ago)
• Last Synced: 2024-01-26T01:02:01.880Z (10 months ago)
• Topics: basketball, clustering, coursera, data-science, exploratory-data-analysis, machine-learning, pca-analysis, unsupervised-machine-learning
• Homepage:
• Size: 1.07 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# 🏀 Basketball Players Analysis

![dunk](https://github.com/raj-pulapakura/Basketball-Players-Analysis/assets/87762282/b00d2768-8dd0-4273-90e8-c2d448d88f37)

## 📖 What's inside?

This repo contains the notebook, data, and final report for my **analysis on the basketball players** using **unsupervised learning techniques** including:

- Principal Component Analysis (PCA)

- K-Means Clustering

- Hierarchical Clustering

![Picture1](https://github.com/raj-pulapakura/Basketball-Players-Analysis/assets/87762282/68a1116c-3067-4431-81d7-65a9a04fcdee)

![Picture2](https://github.com/raj-pulapakura/Basketball-Players-Analysis/assets/87762282/c302a9d5-b6a3-4a9e-afe5-50420996ed73)

## 🤔 Why?

I created this repo for 3 main reasons:

1.  Basketball is my favourite sport.

2.  The final report included in this repo was an assignment for a Coursera project so I thought I might as well share it with the rest of the world.

3.  To showcase my Data Science skills, specifically Exploratory Data Analysis and knowledge of Unsupervised Learning algorithms.

## 🤗 What can you do?

I would love for you to read the analysis and discover more about legendary basketball players, their stats, and how they compare to on another.

I would really appreciate it if you could give me feedback on what I can improve in the report. To send me feedback, you can either create a new Issue in the repo, or email me at [email protected]