My idea for this project started when I found out about the existence since 2010 of the Million Song Dataset, a freely-available collection of audio features and metadata for a million contemporary popular music tracks. Since music is one of my passions, it seemed appropriate to base one of my first Data Science projects on this subject. The core of the dataset was provided by the company The Echo Nest. Its creators intended it to perform music identification, recommendation, playlist creation, audio fingerprinting, and analysis for consumers and developers. In 2014 The Echo Nest was acquired by Spotify, which incorporated that song information into their systems.

Spotify has announced the acquisition of Niland, a machine learning startup based out of Paris. The music company made the announcement itself this week, explaining that Niland shares its'passion for surfacing the right content to the right user at the right time.' Spotify plans to use the company's technology and know-how to improves its own recommendation abilities, doing so with the power of artificial intelligence behind it. Spotify announced the acquisition on Wednesday, saying that the Niland team will be joining the music company's own team in its New York office. The terms of the deal weren't revealed, such as how much Spotify paid for the company or when the deal was finalized. We do know, however, that personalized recommendations on Spotify are about to get much better than to the startup's work in machine learning and artificial intelligence.

Advancement in computers and technology have been incredibly positive for music creators around the globe. You can learn how to produce music on YouTube, purchase the same sample libraries as your favorite composers and create epic scores from your laptop, anywhere in the world. As a result, there are more music producers than ever. Computers helping humans create original music has become today's standard, but there are several companies looking to turn the tables on this process. Computer-generated songs are a fast-growing sector of the industry, looking to disrupt creation, licensing and access for musicians and non-musicians alike.

Advancement in computers and technology have been incredibly positive for music creators around the globe. You can learn how to produce music on YouTube, purchase the same sample libraries as your favorite composers and create epic scores from your laptop, anywhere in the world. As a result, there are more music producers than ever. Computers helping humans create original music has become today's standard, but there are several companies looking to turn the tables on this process. Computer-generated songs are a fast-growing sector of the industry, looking to disrupt creation, licensing and access for musicians and non-musicians alike.

Advancement in computers and technology have been incredibly positive for music creators around the globe. You can learn how to produce music on YouTube, purchase the same sample libraries as your favorite composers and create xustpic scores from your laptop, anywhere in the world. As a result, there are more music producers than ever. Computers helping humans create original music has become today's standard, but there are several companies looking to turn the tables on this process. Computer-generated songs are a fast-growing sector of the industry, looking to disrupt creation, licensing and access for musicians and non-musicians alike.