NQB-4188 Create Your Own Music Recommendation System Using Machine Learning | Devoxx

Devoxx Belgium 2018
from Monday 12 November to Friday 16 November 2018.

   Create Your Own Music Recommendation System Using Machine Learning

Deep Dive

Big Data & Machine Learning
Big Data & Machine Learning
Beginner & novice level
Room 4 Tuesday from 13:30 til 16:30

Have you ever wondered how Youtube and Spotify can possibly recommend new videos and songs to you? Having heard that machine learning plays an important role, you may be wondering what all the fuss is about. How does it work? How can you get started using it yourself?

This session serves as an introduction to machine learning, based on a practical use case. We will be utilizing Spotify's API to extract features from music, before we visualize and cluster the data, and also train classifiers for discovering new music. We will give you an introduction to several algorithms used for clustering and classification of data. In addition to digging into some traditional machine learning algorithms, such as K-means and SVM, we will also take a look at artificial neural networks, which in recent years have produced remarkable results in various fields. For all of this, we will be using frameworks like Keras and Sklearn.

If machine learning has been a mysterious domain to you, this session will most likely leave you with a greater understanding of the process and aid you in how to set up projects of your own.

Machine learning   machine learning algorithms   machine learning classifiers   Big Data   coding  
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Joakim Lehn
Joakim Lehn
From Knowit

Joakim is a technical team lead with the Nordic consultancy Knowit, currently digging deep into modernizing the sales and ticketing solutions for rail operators in Norway as well as creating a national travel planning service across all public transport modes. He is passionate about the possibilities of AI/machine learning and building an awesome team culture with his colleagues.


Manu Gopinathan
Manu Gopinathan
From Knowit

Manu is a machine learning enthusiast who works as a software developer for Knowit, a Nordic consultancy company. Currently, he is a part of a team tasked with building a new sales and ticketing solution for public transportation in Norway. During his MSc studies at UCSB and the Norwegian University of Science and Technology, he specialized in artificial intelligence, with his thesis doing an extensive study on gender identification of authors using deep learning and natural language processing.


Malte Loller-Andersen
Malte Loller-Andersen
From Knowit

Malte is a passionate software engineer and IT consultant for the Nordic consultancy Knowit. He spends his time writing code and is currently in charge of Knowits internal Artificial Intelligence group, The Artificial Chapter. Here, he manages summits and workshops, gives presentations and talks about artificial intelligence.


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