Building a Personal Content Recommendation System, Part One: Introduction
Read OriginalThis article introduces a multi-part series on building a personal content recommendation system. The author outlines a plan to analyze saved articles from Pocket, extract and summarize text, generate embeddings, and build a system to filter new RSS feed content based on personal interests. It covers technical steps like using APIs, LLMs for summarization, embedding models, and automation with cron jobs.
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