I can almost instantly tell whether I am going to like a song or not just by listening to it for a few seconds. I have collected many rare records over the years and done a bit of deejaying on the radio and in clubs. In my book, it's not about how you play, but what you play. To be honest, I have always found that kind of DJ rather boring: the better they are technically, the more it sounds just like one interminable song. There are a number of automatic DJ tools around, which cleverly match the tempo of one song with another and mix the beats. The code for the website is available here. UPDATE: Check out the results after applying to 320,000 tracks on Spotify here. UPDATE: You can now use this model even more easily than before in the Hugging Face hub. ![]() The fact that people have been consistently continuing to use it is testament to how well it works, but it was about time I included tracks released since 2018! I have added a train directory to this repo where you can find a README with detailed instructions on how to obtain datasets and train your own model from scratch. UPDATE: After nearly 5 years, I have finally got around to re-training the model deployed at with a million playlists and a million tracks. Robert Dargavel Smith - Advanced Machine Learning end of Masters project ( MBIT School, Madrid, Spain)
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