Machine Learning Series VII: K-Means Clustering | Bloomberg Professional Services
Webinar

Machine Learning Series VII: K-Means Clustering

This is our last episode of our Machine Learning Series and will be hosted 
live. We will walk you through the basics of K-means Clustering and will show 
you how to leverage it in order to build a diversified portfolio and compare 
its return to the S&P500. 

The BQuant Machine Learning Series is the newest entry for our client facing 
educational content. This webinar collection will familiarize participants with 
the key ML concepts utilized in Finance by Quants & Data Scientists while also 
offering real-world examples and resources to complement the lesson plan. 

References and linkages will be made with associated Python libraries, helpful 
concept visualizations, and online resources to round out your curriculum. 

This is your opportunity to kick-start your fluency in the ML space and we plan 
to prepare deeper dives for topics clients want to learn even more about.

All sessions including this one are recorded and available on-demand.

Speakers

Firas Triki

Quant Developer

Bloomberg L.P.

Firas implements quantitatively-based workflows in Bloomberg's BQuant platform for buy-side clients. Prior to Bloomberg, Firas was a Quant Developer on the sell-side working both on Equity Derivatives and Fixed Income products. He earned a Master’s Degree in Computer Science, a Master’s Degree in Financial Engineering as well as a Certificate in Quantitative Finance.

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