What's next?

1. Put yourself in context

After a hard week at IronHack...

Relax

This club where they play the music that you like

Read a book

Go for sports

Go party

2. The reality

The session is not customised for that night's public

You want to go to a club where they play the music that you like

The DJ maybe has a session prepared for the general public

3. Solution

Build a music recommender that allows the DJ to adapt the session to the public

A recommender that takes the songs that the public requests, during the night, and gives back a song adding it to session

HOW?

4. Target sectors

- DJ's

- Clubs/disco

- Bars/Pubs

5. Music Recommender: Workflow

User's Song

Hot 100

Hot 100 DB song

Spotify DB song

Get audio features

Classify according to model (All songs)

Choose a song

Shows possible songs

Confirm artist

Spotify

Ask artist

DJ's playlist

6. DEMO TIME!

7. Limitations from this version

- Size of the database

- Missing data while getting information from Spotify

- Less accurate classification using just audio features and the amount of tracks in the DB or cluster method.

- Possible repeated songs as recommendations

8. Future improvements

Add the recommended songs automatically to the playlist/session that the Dj is playing

Expand the database:

Use other kind of Machine Learning technics.

Add an evaluation from the DJ's on the effect of the song recommended

Improve the model and make more accurate recommendations
Have more options in terms of recommendations