AWS AI and ML

This is Chapter 1 of the AWS AI and ML series. These are the concepts and service distinctions I kept returning to while building on Bedrock and working through the AIF-C01 exam. Writing them down in one place made the concepts stick. Different types of ML algorithms Three broad families, each suited to a different class of problem. Supervised learning - trains on labelled input-output pairs. Two sub-types: Classification - predicts a category (spam/not spam, image labels). Algorithms: logistic regression, decision trees, random forests, SVM, neural networks. Regression - predicts a continuous value (house price, demand forecast). Algorithms: linear regression, gradient boosting, neural networks. Unsupervised learning - finds structure in unlabelled data: ...