Predictive maintenance is often presented as a chart that turns red just before a machine fails. The real engineering problem is more demanding: histories from the same asset must not leak across data splits, sensor quality and operating conditions must be validated, uncertainty must be visible, and a forecast must pass through an approved maintenance policy before it becomes a work order. This tutorial builds a compact but complete remaining useful life (RUL) pipeline. We will simulate a...

A convincing factory inspection demo is easy to make: train a classifier, upload a product image, and display defective or normal. A production inspection system is harder. It must cope with illumination changes, camera movement, unseen normal variation, uncertain scores, traceability, model drift, and the very different costs of a false reject and a defect escape. This tutorial builds a small but complete reference implementation. We will generate aligned metal-plate images, learn normal...

Product matching answers a deceptively difficult question: do two listings represent the same sellable product? For a retailer, that decision affects search, comparison pages, pricing, inventory, reviews, advertising, and analytics. A false merge can attach the price or reviews of one variant to another. A missed match can split demand across duplicate catalog pages. The problem therefore needs more than an LLM prompt or a single image-similarity score. In this tutorial, we will build a...