Machine Learning: Past, Present and Future - by Prof. Thomas Dietterich, Chief Scientist at BigML.

This talk will dive into the Machine Learning technology and its evolution. Going from its first steps as Data-Driven Software Engineering, analyzing the role of ML for Data Science, the ML trend for Optimizing Operations, and finally the focus of ML in the future.
 

Solve for X with AI: a VC View of the Machine Learning Landscape - by Ed Fernández, Partner & Co-founder at Naiss.io and Board Director at BigML. 

In this session we will provide an overview of the Machine Learning landscape, current M&A and Venture Capital trends and rationale, startups to watch and the implications of Machine Learning technologies for the 99%.

From 0 to Machine Learning in a Few Clicks - by Poul Petersen, Chief Infrastructure Officer at BigML.

So you've heard of Machine Learning and are eager to make your first data driven decision? In this presentation you will see the quickest way to get started with Machine Learning as well as some examples of the type of end-to-end predictive applications that can be built quickly using a ML API, saving you the grief of trying to productize a roll-your-own solution when it is time to put your models into production.

 

Democratizing Active Investment Thanks to Machine Learning - by Jean-Marc Guillard, Chief Executive Officer at Stats4Trade.

Machine Learning Delivering Business Impact in Human Research Management - by Auke IJsselstein, Lead HR Analytics at ABN AMRO.


 

 

Machine Learning Across all US Households - by Seamus Abshere, Chief Technology Officer at Faraday. 

 

Decoding the Game - by Raúl Peláez, Head of Sport Technology at FC Barcelona.