Big Data Science with Python

DevconTLV June 2015 Conference, Monday, June 22, 2015, 12:20

One of the most exciting areas in Big Data is the development of new predictive applications; apps used to drive product recommendations, predict machine failures, forecast airfare, social match-make, identify fraud, predict disease outbreaks etc. These applications output real-time predictions and recommendations in response to user and machine input to directly derive business value and create cool experiences. These hold the true promise of Big Data.

The most interesting apps utilize multiple types of data (tables, graphs, text, & images) in a creative way. In this demo, we will share the trends we’re seeing in predictive application development, show how to build and deploy a predictive app that exploits the power of combining different data types and representations (like graphs and tables) to create powerful applications.

Danny Bickson

Danny Bickson

Co-founder

Dato

Danny Bickson is an expert of big data analytics and large scale machine learning, with more than 15 years experience in the high tech industry. Danny is holding a PhD in distributed systems at the Hebrew University and was a research scientist at the machine learning department at Carnegie Mellon University. 

Danny published more than 35 publications in top journals and conferences, with more than 1500 follow up papers citing his work, as well as 3 granted US patents. Danny participated in a several high profile competitions and won prizes like ACM Knowledge and Data Mining CUP 2011 as well as 2012 and ACM Web Scale and Data Mining 2013.

He is the co-founder of Dato, an open source based big data analytics company based in Seattle. With 30 employees and customers like Adobe, Pandora, Bosch, ExxonMobil, Cisco and Zillow, Dato is a leading market provider for large scale machine learning solutions.

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