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Interpreting Unsupervised Learning Models
Arctic Penguin Exploration: Unraveling Clusters in the Icy Domain with K-means Clustering
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Project Description
Unsupervised learning is a critical task in machine learning, and it plays a significant role in this project. The objective is to delve into the information about penguins by utilizing unsupervised learning techniques on a thoughtfully curated dataset. By conducting thorough data exploration, extracting meaningful features, and employing advanced algorithms, this project aims to uncover concealed patterns, clusters, and relationships that exist within the dataset.
Project Tasks
- 1Perform unsupervised learning techniques to identify clusters of Penguin species!
Technologies
Python
Topics
Machine Learning
George Boorman
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Curriculum Manager, DataCamp
George is a Curriculum Manager at DataCamp. He holds a PGDip in Exercise for Health and BSc (Hons) in Sports Science and has experience in project management across public health, applied research, and not-for-profit sectors. George is passionate about sports, tech for good, and all things data science.