Drift

is an approach to accuracy that devours data, learns patterns, and predicts. Nonetheless, with the perfect models, even those predictions could crumble in the true world with no sound. Firms using machine learning...

Despite the AI hype, many tech corporations still rely heavily on machine learning to power critical applications, from personalized recommendations to fraud detection.  I’ve seen firsthand how undetected drifts may end up in significant costs...

p-valueEnters the infamous p-value. It’s a number that answers the query: what’s the probability of observing the chi-2 value we got or a fair more extreme one, provided that the null hypothesis is true?...

This piece demonstrates using pre-trained LLMs to assist practitioners discover drift and anomalies in tabular data. During tests over various fractions of anomalies, anomaly locations, and anomaly columns, this method was usually capable of...

Data drift occurs when the statistical properties of the input data change over time, resulting in a shift in the info distribution.Note:With default logic, z test is used for goal and KS test is...

. Why does model decay occur? Why does the model which was doing good for previous few days/months starts behaving in another way? Lets attempt to deep dive and understand the explanations for this...