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Wrong! Less than an hour later I got another message. I figured since it was a bit under 800 miles to Breckenridge, I'd get it taken care of there. When you're out, speed gets limited to 4mph. If you ignore the warning, around 100 miles, speed gets limited to 55mph. A few miles down the road I got a DEF Range 900 miles warning. On the way from Goshen to Breckenridge, CO, while filling up on diesel, I filled the Diesel Exhaust Fluid tank at a Flying J ($2.69/gal), putting in 3.1 gallons. Just to make sure there was nothing else hiding behind the check engine light, I used OnStar to run remote diagnostics before starting out every day.

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I pressed the OnStar button to run remote diagnostics and they explained it was a 'Reductant Tank Temperature Sensor error' ( error code p205) and that I could have it fixed at my convenience - end of summer would be fine. On the way to the Goshen Rally, our 20 started throwing a Check Engine Light. The data is available here: EvalDataYear1.This story just has too good an ending to not share.

The real, publication-worthy results, were computed over a test set of 100K users.

This can be considered the validation set.

The challenge on Kaggle had a public leaderboard where results were updated instantly.

The challenge data always comes in two parts: for a given user, half of his listening habits is 'visible' and can be trained on, and a 'hidden' part (kept secret) we use to measure the performance.

The training set (~1M users) is still available, see the Taste Profile Subset.

The first edition of the contest has ended in August 2012, and here is the data from the challenge so you can reproduce the results. Data-specific questions that don't get answered on the mailing list can be sent to Thierry Bertin-Mahieux. unclear rules, typos, etc., should be sent to Brian McFee. General questions should be sent to the MSD mailing list. However, NEMA will conduct additional analysis on the submissions, with the results to be presented at ISMIR 2012. The contest ends in August, and the main result will be announced then. For the curious, the main MIR conference is ISMIR. This field encompasses tools from machine learning, recommender systems, multimedia analysis, psychology. Researchers from the Music Information Retrieval (MIR) community. We want to reproduce the challenge facing a music technology start-up: if you can crawl the web, pay humans, analyze the audio, how do you best recommend songs to your listeners based on a few songs they have already played? the KDD Cup 2011, but they were closed: the metadata about the artists/songs was hidden and no audio features were available. Pure collaborative filtering? content-based recommendations? Metadata like years and nominal genre? There have been other ``music'' contests, e.g. JuliР“РЋn Urbano, University Carlos III of MadridР”В«ecause we don't know yet what is useful for music recommendation. Stephen Downie, University of Illinois at Urbana-Champaign Thierry Bertin-Mahieux, Columbia University The main organizers are barred from winning any prize in the challenged. The challenge is administered by labs at UCSD and Columbia, helped by the members of the advisory committee. Here what you should be looking at in order to participate: October 2012: workshop / special session, awards

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The full details of the contest are available on Kaggle. The MSD Challenge takes the form of a contest where anyone can predict what the test users have also listened to, using whatever technique & data they need. Offline: evaluation is done on a fixed set of actual listening data.

Open: everything is known about the songs (metadata, features. Music recommendation: predict what people might want to listen to

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The Million Song Dataset Challenge is an open, offline music recommendation evaluation: To participate in the contest, see our Kaggle page. This page gives some background information and pointers. Welcome to the MSD Challenge, the largest open offline music recommendation evaluation.

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