by Skillo StaffComparing AI models fairly means controlling prompts, settings, sample size, and scoring, not cherry-picking a few examples. This guide explains a repeatable method you can trust.
by Skillo StaffAI benchmark scores are widely cited but easily misunderstood. This guide explains contamination, test limits, and real-world variability, and suggests a private test set for your own use.
by Skillo StaffBenchmark scores do not tell the whole story. This guide shows how to compare local AI models on accuracy, speed, context, memory, and license using your own repeatable scorecard.
by Skillo StaffPrecision and recall are two measures of how well a classification model performs, capturing different aspects of its accuracy. This guide explains them.
by Skillo StaffA confusion matrix is a table that summarizes how a classification model's predictions compare with the actual answers. This guide explains the confusion matrix.