Filtering by: Day 2

Using ML to build an autonomous drone — Greg Lamp
Mar
15
3:00 PM15:00

Using ML to build an autonomous drone — Greg Lamp

They might not be delivering our mail (or our burritos--tacocopter.com) yet but drones are now simple, small, and affordable enough that they can be considered a toy. You can even customize and program some of them! The Parrot AR Drone has an API that let's you control not only the drone's movement but also stream video and images from both of its cameras. I'll show you how you can use Python and node.js to build a drone that moves all by itself.

Greg Lamp is the co-Founder and CTO of Yhat. In this role, Greg leads development of Yhat's core products and infrastructure and is the principal architect of the company's cloud and on-premise enterprise software applications. Greg was previously a product manager at OnDeck, a fintech startup in New York and before that an analyst at comScore. Greg is a graduate of the University of Virginia.

Twitter: @theglamp - LinkedIn

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Speed-up distributed deep learning with Spark on AWS —  Vincent Van Steenbergen
Mar
15
2:30 PM14:30

Speed-up distributed deep learning with Spark on AWS — Vincent Van Steenbergen

Training deep networks is a time-consuming process, with networks for object recognition often requiring multiple days to train. For this reason, leveraging the resources of a cluster to speed up training is an important area of work. In this talk we'll show how to use an AWS Spark cluster to train a model quickly from a laptop at a very little cost (around 10€).

Vincent Van Steenbergen is a R&D and Backend Engineer at IDAaas (Intelligent Data Analysis as a Service) a research and development spin-off from the University Paris 13. IDAaaS develops services in Intelligent Data Analysis such as Data Mining, Knowledge Discovery in Databases and Predictive Analytics. Vincent has been developing all kind of software for as long as he remembers.

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Demystifying Deep Learning — Roberto Paredes Palacios
Mar
15
2:00 PM14:00

Demystifying Deep Learning — Roberto Paredes Palacios

Deep Learning (DL) is becoming a big tsunami in the Machine Learning community. This talk aims at introducing DL, its motivation and main techniques. However, part of this talk is also devoted to demystify DL. What are the main advantages but also the main drawbacks of DL?. And what are the key issues that the practitioners have to consider?

Roberto Paredes is an Associate Professor at Departamento de Sistemas Informáticos y Computación DSIC of the Universidad Poliécnica de Valencia UPV. He belongs to the Pattern Recognition and Human Language Technologies Research Centre PRHLT. Roberto Paredes is the Director of the PRHLT and the President of the Spanish AERFAI Association. His main research interests are around the statistical learning, machine learning and more recently neural networks and deep learning.

Website

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Evolving a data-driven company from MapReduce to Spark — Ferran Galí Reniu
Mar
15
1:30 PM13:30

Evolving a data-driven company from MapReduce to Spark — Ferran Galí Reniu

Trovit in short time became one of the leaders in the online classified advertising industry. We adopted Hadoop and MapReduce in order to manage all our content in a scalable way. However, we faced its limitations: that’s the reason why we looked at Spark. Right now, early 2016 we already adopted it for good and it is constantly bringing fresh solutions to our business. The talk will consist of an introduction to Trovit and its Big Data infrastructure, and we will specifically illustrate how Spark works with a demo.

Ferran Galí i Reniu is passionate about web scale distributed systems. Working on Big Data technologies for several years he gained expertise solving problems that require a massive amount of data processing. Architecting the deployment of Hadoop on a cluster of machines, developing new solutions or playing data scientist to make the business thrilling are some of the day-to-day tasks he has to deal with. Right now he is working in Trovit building the best search engine for classified ads.

Twitter: @ferrangali - Linkedin

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Engineering the Future of Our Choice with General AI — JoEllen Lukavec Koester
Mar
15
12:00 PM12:00

Engineering the Future of Our Choice with General AI — JoEllen Lukavec Koester

What is the future we want to create, and what can we do – starting today – to actively shape that future with general AI? This talk outlines a vision for the future of humankind once AI reaches human or superhuman levels, and leads the audience through the steps one research group is taking to get there. From the economics of smart robots and job replacement, to bionic humans exploring the universe through space travel, the talk offers a window into the work of 30 researchers focused on AI development and safety, and explains what attendees can do themselves to help make that future happen.

JoEllen is the AI Safety Ambassador and Head of PR for GoodAI, a Prague-based general AI research and development company. A high school teacher by trade, she has a bachelor’s degrees in English and Philosophy from Seattle University, a master’s degree in Transatlantic Studies from Charles University in Prague, and is the recipient of Fulbright grant. JoEllen is particularly interested in how AI will affect international government and political relations.

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Past, Present and Future of AI: a Fascinating Journey — Ramon Lopez de Mantaras
Mar
15
11:20 AM11:20

Past, Present and Future of AI: a Fascinating Journey — Ramon Lopez de Mantaras

Possibly the most important lesson we have learned after 60 years of AI research is that what seemed to be very difficult to achieve, such as accurate medical diagnosis to playing chess at the level of a Grand Master, turned out to be relatively easy whereas what seemed easy, such as visual object recognition or deep language understanding, turned out to be extremely difficult. In my talk I will try to explain the reasons for this apparent contradiction by briefly reviewing the past and present of AI and projecting it into the near future.

Ramon Lopez de Mantaras is Research Professor of the Spanish National Research Council (CSIC) and Director of the Artificial Intelligence Research Institute of the CSIC. Technical Engineer EE (Electrical Engineering) from the Technical Engineering School of Mondragón (Spain) in 1973. Master of Sciences in Automatic Control from the University of Toulouse III (France) in 1974, Ph.D. in Physics from the University of Toulouse III (France), in 1977, with a thesis in Robotics (done at LAAS, CNRS). Master of Science in Engineering (ComputerScience) from the University of California at Berkeley (USA) in 1979. Ph.D. in Computer Science, from the Technical University of Catalonia, Barcelona (Spain) in 1981.

LinkedIn

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Revolutionizing Offline Retail Pricing & Promotions with ML — Daniel Guhl
Mar
15
10:30 AM10:30

Revolutionizing Offline Retail Pricing & Promotions with ML — Daniel Guhl

Everybody uses price promotions in retail. However, individual pricing is seldom used, particularly in offline retail. Marketing literature has been advocating the use of individual price discrimination for decades. Furthermore, product recommendations, ever-present in e-commerce, are also not often found in offline retail. We show the machine learning driven system behind a new promotion channel that enables retailers and manufacturers alike to target individual customers in offline retail. Lessons learned, technologies used, and machine learning approaches driving our system will be shown.

Daniel Guhl has a background in economics & marketing, and got interested in data modeling during his Ph.D.. Currently, he is working as a data scientist at a Berlin based Start-up and is pursuing a postdoc at Humboldt University. He enjoys learning everyday and focuses on solving real world problems.

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Jacek Dabrowski has a university background in mathematics, computer science and psychology. He is also a startup veteran with experience in financial technology and online advertising. His current focus is on building distributed real-time systems, big data pipelines and machine learning engines. He is also passionate about deep learning applications.

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How to predict the future of shopping — Ulrich Kerzel
Mar
15
10:00 AM10:00

How to predict the future of shopping — Ulrich Kerzel

Shopping, or as the people on the other side of the counter call it, retail has become the number one breeding ground for predictive applications in the enterprise. What started as simple recommendation engines has evolved into a complex and powerful ecosystem of predictive applications that affect core processes such as pricing, replenishment and staff planning. In this talk, Ulrich Kerzel will share impact and experiences from building and operating predictive applications for large retailers, and explain why the future of retail is as much a science as an art.

Dr. Ulrich Kerzel is a Senior data scientists at Blue Yonder and renowned scientist with research experience at the University of Cambridge and CERN. Ulrich Kerzel earned his PhD under Professor Dr Feindt at the US Fermi National Laboratory and at that time made a considerable contribution to core technology of NeuroBayes. After his PhD, he went to the University of Cambridge, were he was a Senior Research Fellow at Magdelene College. His research work focused on complex statistical analyses to understand the origin of matter and antimatter using data from the LHCb experiment at the Large Hadron Collider at CERN, the world’s biggest research institute for particle physics. He continued this work as a Research Fellow at CERN before he came to Blue Yonder as a senior data scientist.

Twitter: @Ukerzel - Linkedin

 

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The emergent opportunity of Big Data for Social Good — Nuria Oliver
Mar
15
9:10 AM09:10

The emergent opportunity of Big Data for Social Good — Nuria Oliver

Nuria Oliver is a computer scientist and Scientific Director at Telefónica. She holds a Ph.D. from the Media Lab at MIT. She is one of the most cited female computer scientist in Spain, with her research having been cited by more than 8900 publications. She is well known for her work in computational models of human behavior, human computer-interaction, intelligent user interfaces, mobile computing and big data for social good.

Twitter: @nuriaoliver - LinkedIn

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