Data & ML · Do Directory
Top machine learning engineers, active now
Machine learning engineers build models that learn patterns from your data: forecasting demand, scoring leads, spotting fraud, pricing quotes or recommending products. Many of the biggest wins for small businesses still come from this classic work rather than from chatbots.
Hire someone who starts with the business question and a simple baseline, is honest about what your data can support and can put a model into production, not just a notebook.
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Questions
Machine learning: common questions
How much data do we need for machine learning?
It depends on the problem, but a few thousand well-recorded examples is often enough to test an idea. A good engineer will look at your data early and tell you plainly whether it’s worth going further.
Should we use machine learning or a language model?
For numbers and structured records, such as sales, sensor readings or transactions, traditional machine learning is usually cheaper, faster and more accurate. Language models shine with text. Many projects use both.
What about bias and fairness?
If a model affects people, for example in pricing, credit or recruitment, ask how the engineer tests for unfair outcomes across groups. Decisions like these are covered by UK GDPR and the Equality Act, so build that testing in from the start.
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