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Basketball Analytics: Clustering Players by Performance Metrics
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Updated 04/2024Start Project for Free
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1 Task1,500 XP390
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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
- 1Perform basketball analytics clustering.
Technologies
R
Topics
Machine Learning
Dr. Chester IsmayEducator, 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.