Building a Personal Content Recommendation System, Part Two: Data Processing and Cleaning
Read OriginalThis article details the data processing and cleaning phase for a personal content recommendation system. It explains sourcing a dataset from archived Pocket items via its API, extracting article text using the Jina Reader API to convert webpages to markdown, and preparing the data for building the recommendation model. It is a technical guide focused on the practical steps of assembling a training dataset for an IT project.
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