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3rd Valencian Summer School in Machine Learning is on the Horizon!

by on May 26, 2017

Since 2011, BigML has been at the forefront of the Machine Learning revolution, which is now in full swing. Big and small companies alike are seeing the tremendous payoff from using Machine Learning to make data-driven decisions. As all industries become transformed by predictive applications, BigML’s mission to democratize Machine Learning is more relevant than ever.

VSSML'17

In our continued effort to make Machine Learning beautifully easy for everyone, BigML is proud to announce the third edition of our summer school, which will take place on September 14 and 15 in Valencia, Spain. This two-day event provides a hands-on, crash course introduction to Machine Learning for advanced students, industry practitioners, and business leaders. BigML provides the foundation you need in Machine Learning concepts, tools, and techniques to become a master of your data. Through two days of intensive training, you will gain practical experience with real datasets and learn to make your first predictive application. This event serves as a good introduction to the kind of work students can expect when enrolling for a Machine Learning masters.

Last year’s event was very well received, having attracted a global audience with over 220 applicants, 140 attendees representing 53 companies and 21 academic organizations from 19 different countries. We are looking forward to break last year’s record with this new edition.

The summer school 2017 costs a nominal fee of 30 Euros and is by invitation only. The deadline to apply is August 15. Applications will be processed as they are received, and invitations will be granted right after individual confirmations to allow for travel plans.

Ready to begin your Machine Learning journey with this fun, challenging event? Please register soon since space is limited. Given the success of our previous summer schools in Valencia, Spain and São Paulo, Brazil, we are greatly looking forward to this upcoming event!

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