Tutorial 1: California Housing Regression
This tutorial walks through the California Housing dataset regression example end-to-end — from loading CSV data to running inference on unseen samples. By the end you will understand how CSVLoader, nn::Model, and the training loop fit together.
Tutorial 2: MNIST Digit Classification
This tutorial covers multi-class image classification using the MNIST handwritten digit dataset. You will learn how to set up batched loading with DataLoader, build a classifier, train with CrossEntropyLoss, evaluate test accuracy, and run per-sample inference with a visual terminal display.