A walkthrough of the data acquisition and preparation phase for building a product classification API using Amazon product metadata. Covers parsing 9.4 million products from gzipped JSON, loading into pandas DataFrames, extracting and formatting category paths, and applying multiple filtering steps (removing missing data, excluding non-title-classifiable categories like Books and Movies, keeping only deepest category paths, and dropping categories with fewer than 10 products) to arrive at a clean 4.59 million product dataset ready for model training.
