While preparing to send his first child to college, Jeremy Marks quickly realized that all the free “dorm essential” checklists online were incomplete. He spent hours and hours cobbling together a comprehensive list to ensure his son didn’t show up to school having missed something important.
Then there were more hours upon hours reading reviews and shopping for individual products. And the worst part was trying to organize when and where it would all arrive on campus since Jeremy’s son was attending school across the country. What needed to be purchased in advance? What could be picked up at local stores? What should ship to the dorm vs. mail centers?
Jeremy shared the massive Excel spreadsheet with his wife Julie, who nearly passed at the overwhelming number of items, product links, and tracking notes.
With their second child only a year younger, Jeremy wanted to make the daunting list of building a college packing list, selecting items, and managing the whole process of getting ready for move-in day easier for himself and other families.
So, The Dorm List was born to help rising freshmen and their families save time and money while reducing stress.
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I see this in https://everynoise.com/#updates > 2024-01-05 status update: With my layoff from Spotify on 2023-12-04, I lost the internal data-access required for ongoing updates to many parts of this site. Most of this, as a result, is now a static snapshot of what, for now, will be the final state from the site's 10-year history and evolution, hosted on my own server. Some pieces may get disabled and reenabled... - Source: Hacker News / 2 months ago
Anyone aware of a similar feature for foobar2000? I have an extensive library mostly tagged from Discogs, including release IDs. In theory, this should be sufficient to cluster music by genres, pull similar releases from Discogs "similar" feature and correlate data from https://everynoise.com. Obviously, in case of album mixed genres things will mix up, but I'm not sure there's a model that can correlate existing... - Source: Hacker News / 3 months ago
The article mentions Glenn McDonald's musical genre page (https://everynoise.com/, no longer refreshing with new Spotify data) as an example of a flexible graph-like exploration format, without being burdened by explicit connections. The author also has a thorough description of pros and cons of the general concept. - Source: Hacker News / 6 months ago
This is from Glenn McDonald's blog, founder of "Every Noise at Once". He was laid off from Spotify (discussed here briefly [0]) --- https://everynoise.com/ is now in "archival copy" mode [1][2]. Super sad to read / see this. [0] https://news.ycombinator.com/item?id=38650917 [2] https://twitter.com/EveryNoise/status/1736086849339244935. - Source: Hacker News / 6 months ago
Data exported using: https://benjaminbenben.com/lastfm-to-csv/ Album art compiled using: https://www.neverendingchartrendering.org/ Genre data compiled using: http://organizeyourmusic.playlistmachinery.com/# https://everynoise.com/ https://www.tunemymusic.com/transfer Gender, year and country of origin information manually compiled using Last.fm and wikipedia. Data analysis done in excel and image created in GIMP. Source: 7 months ago