Machine learning is a subset of artificial intelligence that involves the use of algorithms to enable machines to learn from data without being explicitly programmed. In this article, Martin Goodson provides an introduction to machine learning, explaining how it works and why it is important.

Goodson begins by discussing the three main types of machine learning: supervised learning, unsupervised learning, and reinforcement learning. He explains how each type works and gives examples of how they are used in real-world applications.

The article also covers the basics of how machine learning models are built, trained, and deployed. Goodson explains how data is used to train models, how different algorithms are selected, and how models are evaluated for accuracy and performance.

Finally, the article discusses the potential benefits and challenges of machine learning. Goodson notes that while machine learning has the potential to revolutionize many industries, there are also concerns around issues such as bias, privacy, and transparency.

Overall, this article provides a comprehensive overview of machine learning that is accessible to readers with little to no prior knowledge of the subject.