IT Career Guides & Free Resources
Expert roadmaps, tutorials, salary guides and interview prep across Data Science, Generative AI, Python, Cloud & Analytics — written by GloryTecks trainers in Hyderabad.
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Evaluating LLM Outputs: Metrics, Tools and Best Practices
Every change to a prompt or model needs evidence that it helped. This guide explains the main ways to evaluate LLM outputs, then checks a small local LLM judge against expert human verdicts from MT-Bench and finds it agreeing often, flipping often when answers swap places, and trustworthy only when consistent.
Metrics That Matter: Vanity vs Actionable Metrics
Vanity metrics versus actionable metrics explained with a real example: a customer total that rose every single month while new customer acquisition fell by more than half, what makes a metric actionable, how the same number can be vanity for one business and vital for another, and a five-question test for any metric.
Marketing Analytics: Metrics and Dashboards That Matter
The marketing analytics metrics that matter, defined precisely: click-through rate, conversion rate, cost per acquisition, return on ad spend and engagement rate, then applied to 12,330 real shop sessions to compare traffic sources by what they deliver, plus a dashboard layout and attribution traps.
Evaluation Metrics: Accuracy, Precision, Recall and F1 Demystified
How to choose between accuracy, precision, recall, F1 and their relatives, with every number from a real medical screening dataset: why a do-nothing model scores 65% accuracy, how the threshold trades precision for recall, when F2 beats F1, how macro and micro averages differ, and why PR-AUC suits rare positives.