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Customer Segmentation with K-Means by diya.mscit24 is a document available to read on EtoBox.

What is Customer Segmentation with K-Means about?

The document outlines a series of practical exercises in advanced machine learning, including customer segmentation using K-Means clustering, hierarchical and DBSCAN clustering, association rule mining with Apriori, Q-learning for pathfinding, and comparing SARSA with Q-learning. It also covers implementing a deep Q-network for the CartPole problem, applying Q-learning to the FrozenLake environment, and building a neural network for classification using the Iris dataset. Each practical includes code snippet

Author

diya.mscit24

Language

EN