Machine learning can be added to a Jamstack site using various methods, including TensorFlow.js, ml5.js, Netlify Functions, APIs from AI solutions providers such as Microsoft, Google, and Amazon, and small utility packages written in Node.js. These methods provide flexibility and accessibility to machine learning capabilities for developers. For example, using TensorFlow.js allows for pre-trained models, transfer learning, and creating custom models on the client-side, while Netlify Functions can run serverless functions with a longer execution limit. Additionally, APIs from AI solutions providers offer an easy-to-use solution for content moderation and other applications. By leveraging these methods, developers can add machine learning to their Jamstack sites in a relatively short amount of time, making it easier to create intelligent and interactive web applications.