Articles on Machine Learning

A practical guide to AI for executives: understand machine learning, NLP, and computer vision — then learn how to implement AI strategically.

Using ChatGPT for emails isn't 'doing AI.' Real implementation means building models, integrating systems, and learning from failure. Here's how.

NLP is the real technology behind LLMs, and it's quietly reshaping customer engagement. From chatbots to sentiment analysis, here's why it matters.

Drowning in data but starving for insights? A no-nonsense guide to machine learning techniques that turn business data into better decisions.

RLHF is how AI learns from human preferences. Here's how Reinforcement Learning from Human Feedback reshapes business decisions and customer experience.

In this post, I provide an overview of comparing different machine learning methods.

Do you need machine learning? Maybe. Maybe not. Everyone's talking about machine learning but its not the answer to every problem.

Machine learning will not replace humans in the security chain, but it can help IT professionals monitor data access and system security effectively.  

Accuracy and Trust in Machine Learning - are they mutually exclusive or can you have both when building machine learning models?

Do you know what the big four machine learning risks are? Do you know how to mitigate these risks? If not, check out this article to learn more.

What can you actually do with machine learning and AI? Examples of areas within organizations that can benefit from these technologies.

Guidance for non-technical people on how to ask the right questions to evaluate whether a machine learning model is good enough for the job.

When should deep learning be used? the answer isn't a simple one. The answer depends on the problem, data size and number of other factors.

If you'e looking for a good, short introduction to Random Forests, check out Machine Learning With Random Forests And Decision Trees.