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Data is the foundation upon which these types of computer intelligence can be built. We want the machines to learn and do more, but in order for them to do that, we must provide them with good ...

Ensure a strong data foundation. Over 15 years ago, I got my PhD in data mining where we used early machine learning and AI techniques on older, slower and much larger computers.

When you listen to quantum enthusiasts, you may feel tempted to treat QML as an emerging silver bullet, which it isn’t.

Foundations of supervised learning: empirical risk minimisation, empirical minimisation with inductive bias, PAC learning, learning via uniform convergence Convex optimisation: convexity, ...

AI and machine learning skills are in short supply. If your organization is considering bringing these in house be sure you have what's needed to be successful.

Once machine learning models make it to production, they still need updates and monitoring for drift. A team to manage ML operations makes good business sense ...