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CodeSignal

K-means Clustering 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: Mastering K-means Clustering with Python: From Theory to Practical Implementation
    • Spectral Clustering of Stars
    • Mystery Glitch in the Iris Galaxy
    • Cluster Centroids Initialization
  • Unit 2: Visualizing K-means Clustering on an Iris Dataset with Matplotlib
    • Visualizing Iris Clusters with K-means and Matplotlib
    • Color Remix in Cluster Visualization
    • Painting Clusters in Space
  • Unit 3: Mastering K-means Clustering and the Rand Index with Python
    • Visualizing Clusters with K-Means and Rand Index Evaluation
    • Adjusting the Number of Clusters in KMeans
    • Measuring the Cluster Performance
  • Unit 4: Mastering K-means Clustering: Selection of Clusters and Centroid Initialization
    • Visualizing K-means Clustering on an Iris-like Dataset
    • Plotting the Cosmos: Add the K-means Visualization
    • Charting the Course with K-Means Clustering

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