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Gain the fundamental knowledge to start building classification algorithms

Classification techniques are widely used in enterprise organizations. From the limit of your credit card, to your mortgage amount, as well as the things you see online and on your social media timeline. You might not fully realize it (yet), but all these aspects are determined by classification algorithms. Classification algorithms determine, to a large extent, the content we see, the information that is presented to us, and the decisions we make. But have you ever wondered how these classification algorithms work?

 

What you will learn

In this webinar, we will present you with a fundamental understanding of classification algorithms. We will discuss how they work, which parameters you need, and what the differences are between different classification algorithms. In the second part of the webinar, we will discuss one of the most widely used (in terms of application) classification algorithms: the K-Nearest Neighbour Classification (k-NN) algorithm. We will showcase how it works, how it helps solve problems and provide a demonstration in R. After this webinar, you will have the fundamental knowledge to start building classification algorithms by yourself.

 
  • 10 December 2020
  • 9:00 GMT

Presenter

Jan-Willem Middelburg is the CEO and co-founder of Cybiant, based in Amsterdam. He started Cybiant with the mission to make a more sustainable world for the Next Generation through the use of data and automation. Jan-Willem authored and co-authored numerous books, including Serious Gaming (2013), The Service Automation Framework (2017) and recently The Enterprise Big Data Framework (2018).

A pioneer and advocate for professionalisation in Automation and Big Data, he is a frequent keynote speaker and moderator at universities and technology conferences around the world. Jan-Willem holds a Bachelor’s degree in Industrial Engineering, a Master’s in Supply Chain Management from the Rotterdam School of Management, and is currently pursuing a second Master’s degree in Computer and Information Technology at the University of Pennsylvania. 

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