The article documents a recipe data extractor that underperformed, mislabeling buttons and duplicating ingredients. It outlines planned incremental improvements with feature enrichment to approach production readiness.
This post trains an initial supervised learning model on labeled recipe data, walks through the training pipeline and reports the first evaluation metrics. It explains feature extraction, pipeline construction, and highlights practical next steps to improve model accuracy and reduce common misclassifications.
A hands-on introduction to building a supervised learning pipeline using labeled recipe data from the author's old Recipe Folder project. This post explains the dataset, setup steps, and the plan for a multi-part series to train and improve models for extracting recipes from web pages.
Good lord, it has been 6 months since I last wrote a post about LLMs and coding and how the world has changed.
As we get more and more experience with LLM's I am starting to get worried that I am spending more time relying them and letting my brain atrophy...