ML Foundations - ML Digest

Data Drift vs Concept Drift

Consider a spam filter trained in 2010. By 2020, users receive far more promotional newsletters than before. The types of […]

Imagine you are hiring a new employee who will have access to your email, your calendar, your code repositories, and

Imagine that two doctors examine the same patient and both say, “The treatment worked.” One doctor means the fever dropped.

Imagine a model that predicts loan defaults. During training, the pipeline pulls account_balance from the warehouse today, but the examples

In tabular machine learning, the winning recipe is often not a flashy architecture but strong features plus a fast, reliable

When two or more features in a regression model are highly correlated, it becomes difficult to determine their individual impact.

Logistic regression is a probabilistic linear classifier. It starts with a linear score, converts that score into a probability for

Imagine a teacher grading a multiple-choice exam. If the teacher says, “Only this one answer has any value, and all

Decision trees are one of the simplest ways to turn data into a sequence of human-readable rules. You can think

Imagine that you need to open $K$ new coffee shops in a city. You want each person to walk to

There is an old proverb that perfectly captures the intuition behind one of the most fundamental algorithms in machine learning:

1. The Intuition: The Overconfident Weather Forecaster Imagine planning a weekend picnic. You check two weather applications. You cancel the