{"id":13001,"date":"2026-08-10T10:53:14","date_gmt":"2026-08-10T10:53:14","guid":{"rendered":"https:\/\/nokobox.com\/index.php\/item\/maven-analytics-machine-learning-4-unsupervised-learning-2025-10\/"},"modified":"2026-08-10T10:53:14","modified_gmt":"2026-08-10T10:53:14","slug":"maven-analytics-machine-learning-4-unsupervised-learning-2025-10","status":"publish","type":"digital_item","link":"https:\/\/nokobox.com\/index.php\/item\/maven-analytics-machine-learning-4-unsupervised-learning-2025-10\/","title":{"rendered":"Maven Analytics \u2013 Machine Learning 4 Unsupervised Learning 2025-10"},"content":{"rendered":"
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Descriptions<\/h2>\n

Machine Learning 4: Unsupervised Learning, This course is part 4 of a 4-part series designed to help you build a fundamental understanding of machine learning. You\u2019ll start by reviewing the machine learning landscape, exploring the differences between supervised and unsupervised learning, and learning several of the most common unsupervised techniques including cluster analysis, association mining, outlier detection, and dimensionality reduction. Each concept is broken down in plain language to help you build intuition for how these models work, from k-means and apriori to outlier detection and principal component analysis. The course features unique demos and real-world case studies, showing how k-means can identify customer segments, how apriori can be used for basket analysis and recommendation engines, and how outlier detection can spot anomalies in cross-sectional or time-series datasets. If you\u2019re ready to build the foundation for a successful career in data science, this is the course for you.<\/p>\n

What you\u2019ll learn<\/h3>\n