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1
Intro
2
Theory of Machine Learning
3
Colab Notebook exploration of K-Means Algorithm
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Distance Metrics
5
Creating K-Means Pipeline
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Elbow Plots
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Silhouette Plots
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Running K-Means Serial Simulation
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Running K-Means Parallel Simulation
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Spinning up Huge Cloud9 128 GB Ram 32 vCPU Instance
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Running massively parallel K-Means
Description:
Explore k-means clustering from theory to implementation in this comprehensive 26-minute video tutorial. Dive into the theory of machine learning, examine a Colab notebook demonstrating the K-Means algorithm, and learn about distance metrics. Create a K-Means pipeline, interpret elbow and silhouette plots, and run K-Means simulations in both serial and parallel modes. Witness the power of cloud computing by spinning up a massive Cloud9 instance with 128 GB RAM and 32 vCPUs to execute large-scale parallel K-Means clustering. Gain practical insights into scaling machine learning algorithms for real-world applications.

K-Means Clustering - Theory, Algorithm, Implementation, Scaling

Pragmatic AI Labs
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