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Basketball Analytics: Clustering Players by Performance Metrics

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Updated 04/2024
Cluster NBA players by performance stats in the 2022-2023 season.
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1 Task1,500 XP351

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Project Description

Embark on a journey through the 2022-2023 NBA season with R's clustering algorithms to analyze player stats. Group players, write and use functions with the tidyverse, and create dendrograms for insightful visualizations, understanding player metrics through data exploration, and sharpening your data analysis skills.

Project Tasks

  1. 1
    Perform basketball analytics clustering.

Technologies

R R

Topics

Machine Learning

Prerequisites

Introduction to the TidyverseCluster Analysis in RIntroduction to Writing Functions in R
Dr. Chester Ismay HeadshotDr. Chester Ismay

Educator, Data Scientist, and R/Python Consultant

Chester enjoys helping others get into data science, figuring out how to best practice and improve on their skills, and working as a part-time consultant on R and Python programming projects. He is co-author of "Statistical Inference via Data Science: A ModernDive into R and the Tidyverse" available at moderndive.com and for purchase from CRC Press. He likes leading education and data science teams with the goal of improving best practices based on data from the learning sciences.
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