Tech Fixx · Video
How to Fix Bad Training Data: Missing Values, Duplicates & Bias
Watch this 3 min 35 sec tutorial from the Tech Fixx channel, published .
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From the video description
Bad training data can make an AI model inaccurate, unfair or unreliable. This practical guide shows how to diagnose common dataset problems before training and how to choose a correction that matches the situation.
You’ll learn: • Detecting missing and impossible values • Finding duplicate or conflicting records • Standardising formats, units and categories • Checking label errors and class imbalance • Looking for sampling and representation bias • Separating genuine outliers from data-entry mistakes • Recording every cleaning decision
Do not delete unusual data automatically: an outlier can be an error, a rare but valid case or the most important signal in the dataset.
#TrainingData #DataQuality #ResponsibleAI