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CodeSignal

K-means Decoded

via CodeSignal

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Overview

Unlock the secrets of K-means clustering, the backbone of unsupervised learning. You will group data into clusters, identify cluster centroids, and refine cluster quality.

Syllabus

  • Unit 1: K-means Clustering in R
    • K-means Clustering for Spectral Data Analysis
    • K-means Clustering Correction on Iris Dataset
    • Initializing Centroids for Clustering Task
  • Unit 2: Visualizing Clusters in R
    • Visualizing Iris Clusters with K-means in R
    • Adjusting Iris Dataset Clusters with Plasma Color Map
    • Visualizing Clusters of the Iris Dataset
  • Unit 3: Evaluating K-means Clustering
    • K-means Clustering on Iris Dataset with Adjusted Rand Index Calculation
    • Adjusting KMeans Clusters and Evaluating with Adjusted Rand Index
    • Evaluating K-means Clustering with Adjusted Rand Index
  • Unit 4: Choosing Clusters and Centroids
    • K-means Clustering Visualization with Iris-like Dataset
    • Clustering and Visualization of Star Data
    • KMeans Clustering Algorithm Implementation

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