In Episode 23 of '100 Days of Data,' Jonas and Amy explore the fundamentals of machine learning—how machines learn patterns from data without being explicitly programmed. They break down key components including algorithms, patterns, and models, using real-world analogies and business examples to demystify complex concepts. From manufacturing defect detection to retail recommendation systems, the hosts illustrate how machine learning moves beyond traditional programming by leveraging vast amo...
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In Episode 23 of '100 Days of Data,' Jonas and Amy explore the fundamentals of machine learning—how machines learn patterns from data without being explicitly programmed. They break down key components including algorithms, patterns, and models, using real-world analogies and business examples to demystify complex concepts. From manufacturing defect detection to retail recommendation systems, the hosts illustrate how machine learning moves beyond traditional programming by leveraging vast amo...
In Episode 9 of '100 Days of Data,' hosts Jonas and Amy explore the transformative power of metadata—data about data—and why it’s essential for making information searchable, trustworthy, and actionable. Using practical analogies and real-world business examples, they explain how metadata provides context, governs access, enhances searchability, and supports collaboration across teams. From digital catalogs to schema design and data lineage, the episode dives into how metadata underpins syste...
100 days of data
In Episode 23 of '100 Days of Data,' Jonas and Amy explore the fundamentals of machine learning—how machines learn patterns from data without being explicitly programmed. They break down key components including algorithms, patterns, and models, using real-world analogies and business examples to demystify complex concepts. From manufacturing defect detection to retail recommendation systems, the hosts illustrate how machine learning moves beyond traditional programming by leveraging vast amo...
