Predictive Analytics with TensorFlow 5.1: Using K-means for Predictive Analytics

The video tutorial introduces unsupervised learning, focusing on clustering techniques like K-Means. It explains how these techniques group data without labels, using real-world examples such as organizing music files. The K-Means algorithm is detailed, including its iterative process and mathematical operations. A practical example using the Saratoga homes dataset demonstrates clustering for neighborhood prediction. The tutorial concludes with optimizing K-Means using the elbow method to determine the optimal number of clusters.

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