While Spotify does have human music experts making thousands of playlists, Ogle quickly realized that the company couldn't employ enough people to make personalized Discover Weekly playlists for. A few days ago Spotify made a fu move and disabled Spotify playlists exporters. If you ever thought about switching streaming services or just making a backup of your playlists, this may be the last call. In the future, it may be impossible to export your own playlist to a different provider. It's still possible with our exporter.
New music is everywhere. Hundreds if not thousands of new albums are released each week between major labels, mid-level subsidiaries, independent shops, and droves of label-less hopefuls. So with all those sweet new tunes out there, how do you dig through the dreck and find what sings to your soul?
Music is a deeply personal experience, and describing what you like or dislike about a particular song or artist can sometimes be frustratingly difficult. This can make finding new music difficult, and discovering hidden gems near impossible.
The answer? Spotify Discover Weekly. As veteran Spotify users know, Discover Weekly is a curated playlist of 30 songs ranging from new releases to deep cuts, personalized just for you. But how does it work? Data science.
“Recommendation is a really common problem for data scientists,” said Lucas Ramadan, a student in Galvanize’s data science program. Download spotify in india iphone without switching to us id phone. “The most common technique used for recommendation is called collaborative filtering.”
Recommendation engines have become commonplace in our daily lives. Netflix uses them to recommend new movies and TV shows we might like, while Amazon uses them to turn shoppers on to new products. The trick to collaborative filtering is that it recommends new things based on similarity between users, not between items.
In the case of Spotify, that means a huge database filled with everything that users have already listened to, where the rows are filled with users, and the columns are all the songs each user has listened to. A collaborative filtering algorithm finds users that are similar to each other, based upon their usage—the songs in common they have listened to—and then recommends the songs that only one person has listened to to the other.
But collaborative filtering isn’t the only thing responsible for setting you up with that hot new M83 track. Spotify discover actually uses what’s known as an ensemble method—a collection of models of which collaborative filtering is a member of.
“A big problem for collaborative filtering is what’s called the ‘cold start problem,’ which is when you’re starting a new product and you have no user data,” Ramadan said. For Spotify, this manifests when you have a new user who hasn’t listened to very much yet, as well as when you have an obscure, unpopular, or new song that not many people have listened to yet.
Spotify wants to be able to recommend these new songs (and deep cuts) so to get around the cold start problem, it uses what’s called convolutional neural networks to actually analyze the songs themselves.
“The convolutional neural network is run over the acoustics of a song itself and analyzed to determine songs that have similar acoustic patterns,” Ramadan said.
A third method used is a form of natural language processing. In natural language processing, there’s a technique called Word2Vec, which takes words and encodes them into a mathematical representation—a vector. In these mathematical representations, vectors with a similar shape would equate to words with a similar meaning. Basically, it’s mathematical representation of the implicit associations and relationships between words that we know to be true in everyday speech.
What Spotify does is very similar to Word2Vec. It takes playlists and treats them as a paragraph or big block of text, and treats each song in the playlist as an individual word. This results in vector representations of songs that can be used to determine two pieces of music that are similar. As such, Spotify is able to determine which songs are similar to each other, thus enabling it to tackle the cold start problem and recommend songs with very few plays.
One of the things that makes Discover so good is that it employs a technique called outlier detection to differentiate things you actually like. Outlier detection is commonly used in financial security—it’s what banks and credit card companies use to detect fraudulent charges—but it also has uses in recommendation engines.
Essentially, outlier detection is used to determine if a particular usage—that is, listening to a song—is part of a normal pattern of behavior or not. This way, if you usually only listen to classic rock and ’90s alternative, your Discover Weekly playlist won’t get filled up with pop hits when your little brother plays Justin Bieber one time.
“Now, if you keep listening to Bieber 50-50 with other stuff, then it will start to recommend songs similar to Bieber,” Ramadan said. https://xwvomj.weebly.com/blog/spotify-downloader-apk-revdl. “The idea is that it initially flags it as an outlier and largely ignore it, only adding it to your recommendations if you continue that usage pattern.”
With all these algorithms working together, it’s no wonder that Discover Weekly is a hit. The general sentiment seen on places such as Twitter, as well as feedback collected by Spotify itself, suggests that people are very pleased with the 30 new songs recommended each week.
And if not? Well, all you can blame is the data.
Courtesy of Spotify
If the Discover Weekly playlist is your favorite part of Spotify, here’s something that’s bound to make your day: A new, Spotify-compatible tool called Discover Quickly takes everything you love about Discover Weekly and makes it easier, faster, and even more of an Experience-with-a-capital-E. A free-to-use, web-based tool, it's simple to access; all you need to do to get in on it is go to Discover Quickly’s website and login with your Spotify account. You’ll be surfing from tune to tune in no time — and you might just stumble upon your new favorite artist while you’re at it.
Spotify introduced the Discover Weekly feature way back in 2015. Each Monday, it presents a new, two-hour playlist (nostalgically referred to by the company as a mixtape) specific to each individual user based both on what they’ve been listening to lately and on other songs and artists that might be related to those habits. The tool was an immediate hit, although it hasn’t been without its complaints. It’s not always easy to navigate if you want to explore the artists that appear on it a little more thoroughly, for example; what's more, as some users observed, it can occasionally get “stale,” recommending the same tunes, albums, and artists over and over again.
That’s where Discover Quickly comes in. It's not an official Spotify tool, although its developers, Aliza Aufrichtig and Edward Clement Lee, do both work at Spotify. It uses Spotify’s public API to bring an exploratory quality to music discovery that’s a little more like a scavenger hunt that it is like pouring through pages and pages of lists. As Aufrichtig put to Gizmodo, “There’s very little in Discover Quickly that you can’t do on your regular Spotify app, but we chose to foreground the activity of traversing music quickly and visually.”
Discover Quickly provides a fast and easy way for you to preview the tracks in your Spotify-generated Discover Weekly playlist. Instead of needing to click on and listen to individual in the playlist — or listening the playlist itself straight through in its entirety — Discover Quickly displays the album covers of all those songs as a grid and allows you to hear a short clip of each track just by mousing over the album cover of your choice. If you like what you hear, you can click on the album cover both to bookmark the song and pull up more info about both it and the artist — and from there, you can begin clicking though and through and through, almost like you’re traveling through wormholes made of sound.
My own experience navigating the interface has been positively delightful so far. I’ve been listening to a lot of Studio Ghibli scores and covers lately (it is excellent writing music), so right now, my Discover Weekly playlist is full of contemporary classical, acoustic, and anime-related suggestions — for example, a cover of the theme from the 2002 Ghibli film The Cat Returns by the Kyoto Harp Ensemble, something from an album of Stravinsky, John Adams, and Pierre Boulez music performed by pianists Gerard Bouwhuis and Cees van Zeeland, and a single by Australian singer/songwriter Pekoe.
Spotify free pandora. In Discover Quickly, it looks like this:
Spotify Discover Weekly Bad
Clicking on the stuff I like pops it into the little bookmark tab up top:
The number in the tab indicates how many songs you’ve saved.
If you expand the tab, you can play entire songs by clicking on them, click “save all tracks” to add them all to your Spotify library, or add ‘em to either a new or existing playlist of your own creation by clicking “add all to playlist” and either selecting “new playlist” (to make a new one) or the name of a playlist you’ve already made (to add them to an existing one). Or, you decide you’re not as wild about one song as you originally thought, clicking the “x” next to it will remove it from the list.
Spotify Weekly Discover
Scrolling down, meanwhile, lets you explore the artist a bit more fully — you can click their name to see more from them, the name of the album the song on your Discover Weekly track is from to see the complete album, or either of the “Recommend songs” tags to get recommendations based either on the song itself or the artist more generally.
Spotify Discover Weekly History
Spotify free hulu for students. Gizmodo’s Adam Clark Estes described the exploration process as “[falling] into rabbit hole after rabbit hole of music, discovering all kinds of new stuff along the way”— an assessment with which I would agree. I don’t often use Discover Weekly because I’ve always found the tool a bit clunky to navigate within Spotify; with Discover Quickly, though, I might finally start utilizing it regularly.
There are lots of other ways to explore, too — and the best part is, it’s free. All you have to do is go to Discover Quickly’s homepage and login with your Spotify account; then you’re good to go.