{"podcast":{"title":"Data Science Tech Brief By HackerNoon","slug":"data-science-tech-brief-by-hackernoon-6367564","podcast_index_feed_id":6367564,"rss_url":"https://feeds.transistor.fm/data-science-tech-brief-by-hackernoon","website_url":null,"image_url":"https://img.transistorcdn.com/PRg81mb1bHdu71bs3zSzRC6oEjt9WcIHjS2ba3uMWCY/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9zaG93/LzQxMjY4LzE2ODM1/ODI1ODUtYXJ0d29y/ay5qcGc.jpg","author":"HackerNoon","episode_count":100,"summary":"Learn the latest data science updates in the tech world.","last_synced_at":"2026-06-18T06:17:56.540839+00:00","page_url":"https://stenobird.com/podcast/data-science-tech-brief-by-hackernoon-6367564"},"episode":{"title":"How I Decoded My Apple Watch Metrics: Taking a Look At The Raw Numbers (Part 2)","slug":"how-i-decoded-my-apple-watch-metrics-taking-a-look-at-the-raw-numbers-part-2","published_at":"2026-05-09T16:00:50+00:00","page_url":"https://stenobird.com/podcast/data-science-tech-brief-by-hackernoon-6367564/how-i-decoded-my-apple-watch-metrics-taking-a-look-at-the-raw-numbers-part-2","show_page_url":"https://stenobird.com/podcast/data-science-tech-brief-by-hackernoon-6367564","url":"https://share.transistor.fm/s/e0488ba2","audio_url":"https://media.transistor.fm/e0488ba2/7ee7086a.mp3","summary":"This story was originally published on HackerNoon at: https://hackernoon.com/how-i-decoded-my-apple-watch-metrics-taking-a-look-at-the-raw-numbers-part-2 . Learn how to parse Apple Health XML & GPX files. A technical guide to \"streaming\" large CDA files and extracting workout kinematics using Python. Check more stories related to data-science at: https://hackernoon.com/c/data-science . You can also check exclusive content about #data-science , #python-notebook , #python , #apple-watch , #apple-health , #prediction-delta , #health-data , #apple-wearable-data , and more. This story was written by: @farzon . Learn more about this writer by checking @farzon's about page, and for more stories, please visit hackernoon.com . Exporting Apple Health data results in massive, messy XML files that are difficult to process. By using a \"streaming\" parser to filter specific LOINC codes and extracting GPS kinematics from GPX files, I converted 300MB of raw records into clean CSVs. This structured data is now ready to be fed into a custom machine learning model to reverse-engineer VO2 Max.","meta_description":"This story was originally published on HackerNoon at: https://hackernoon.com/how-i-decoded-my-apple-watch-metrics-taking-a-look-at-the-raw-numbers-part-2…","key_points":[],"chapters":[],"topics":[],"duration_seconds":219,"processing_state":"not_requested","actions":[{"name":"request_transcript","method":"POST","url":"https://stenobird.com/v1/public/podcasts/data-science-tech-brief-by-hackernoon-6367564/episodes/how-i-decoded-my-apple-watch-metrics-taking-a-look-at-the-raw-numbers-part-2/transcription-requests","description":"Idempotently request low-priority transcript generation for this episode."},{"name":"read_markdown","method":"GET","url":"https://stenobird.com/podcast/data-science-tech-brief-by-hackernoon-6367564/how-i-decoded-my-apple-watch-metrics-taking-a-look-at-the-raw-numbers-part-2.md","description":"Read the agent-friendly Markdown representation of this episode resource."}]}}