Essays
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How can business decision makers trust machine learning and deep learning predictions?
On model explainability, local explanations, feature contributions, and the role of business judgment.
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Data Science Practitioner Notebook, Part II
Five more lessons on stakeholder engagement, understanding models, deployment, adoption, and data leakage.
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Data science: still the same?
Looking through the changing vocabulary of AI to the enduring problem of learning a function from data.
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The generative roots of NLP
A practitioner’s reflection on probability, hidden Markov models, and the evolution of language modeling.
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Ten signs you think like a data scientist
A lighter look at the statistical habits that follow a data scientist everywhere.
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Beyond wrappers: unlocking strategic value with generative agents
Why the way we represent a changing business matters as much as the model we apply to it.
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Christmas trees, newspapers, and the elegance of revenue management
A seasonal observation leads to the newsvendor problem, an elegant optimal-quantity rule, and the mathematics behind perishable inventory.
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The intersection of predictive AI and agentic AI
Predictive models give agents more than historical facts: they bring estimates of possible futures, uncertainty, and a basis for better decisions.
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Transfer learning: an old trick, a new workhorse
What experienced practitioners and pretrained networks have in common: both bring useful knowledge to a new problem.
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Where the party is at: eigenvectors and singular values
An intuitive appreciation of eigenvectors, singular values, and the remarkable places where matrix decomposition turns up.