aapatel09/handson-unsupervised-learning
Code for Hands-on Unsupervised Learning Using Python (O'Reilly Media)
This project helps data professionals and machine learning practitioners analyze unlabeled datasets to uncover hidden patterns and gain insights. It provides practical Python code examples, using scikit-learn and TensorFlow, to process raw, untagged data and output organized information such as customer segments, anomaly detections, or engineered features. It's designed for anyone with programming and some machine learning experience who needs to extract value from data without predefined categories.
696 stars.
Use this if you need to find patterns, anomalies, or groupings within large datasets that lack existing labels or categories.
Not ideal if your data is already well-labeled and you primarily need to build models for prediction or classification.
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Last pushed
Mar 01, 2026
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