Joakim Lehn | Devoxx

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

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.

Create Your Own Music Recommendation System Using Machine Learning

Deep Dive



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 algorithms, choosing the correct algorithm for your problem

Quickie

When I started out exploring machine learning I often faced the problem of choosing the most appropriate algorithm for my specific problem. In this presentation I will try to explain basic concepts and give you an intuitive approach to using different algorithms for different tasks. By the end of this presentation you’ll know which category of algorithms is most suited for your problem.

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