EPISODE · Feb 2, 2025 · 14 MIN
Mastering Clustering Algorithms in Python
from Lunartech · host LunarTech
This podcast comprehensively covers unsupervised machine learning, focusing on clustering techniques. It explains the theory behind various clustering algorithms—K-Means, hierarchical clustering, and DBSCAN—and provides Python implementations and visualisations for each. Data preparation steps and methods for evaluating clustering performance are also detailed. Finally, the handbook introduces dimensionality reduction using t-SNE for visualising clusters and briefly mentions other unsupervised learning methods such as mixture models and topic modelling.
What this episode covers
This podcast comprehensively covers unsupervised machine learning, focusing on clustering techniques. It explains the theory behind various clustering algorithms—K-Means, hierarchical clustering, and DBSCAN—and provides Python implementations and visualisations for each. Data preparation steps and methods for evaluating clustering performance are also detailed. Finally, the handbook introduces dimensionality reduction using t-SNE for visualising clusters and briefly mentions other unsupervised learning methods such as mixture models and topic modelling.
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Mastering Clustering Algorithms in Python
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