Taylor Scott Amarel

Experienced developer and technologist with over a decade of expertise in diverse technical roles. Skilled in data engineering, analytics, automation, data integration, and machine learning to drive innovative solutions.

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Beyond Accuracy: A Practical Guide to Evaluating Machine Learning Models for Real-World Applications

Introduction: The Limitations of Accuracy In the burgeoning field of artificial intelligence, machine learning models are rapidly transforming industries, from healthcare to finance. However, the true measure of a model’s success lies not just in its theoretical accuracy, but in its practical performance within real-world applications. While accuracy provides a general overview, it often masks