26-28 November, 2019, Vilnius

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26-28 November, 2019, Vilnius

Early Bird Ends In:

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Confirmed Talks

Miel Hostens

Utrecht University, The Netherlands

Talk

Predicting the Moment of Birth using Sensor Data in Dairy Cows

Stillbirth, defined as calves that die during unobserved birth is often seen as an indicator of lowered animal welfare in dairy cows. Sensors have been proposed as a tool to support dairy farmers but accurate calving prediction models are often lacking. In this session, a machine learning data pipeline will be described using the spark ML framework. Heavy lifting and feature preparation for sensor data from 1331 cows on 8 herds from 21 days before until the day of calving was performed using sliding windows and time series analysis.

Session Keywords

Spark
Scala
Dairy
Cows

David Gorena Elizondo

Microsoft, USA

Talk

Knowledge and AI Powering Microsoft & Office 365 Products

Knowledge, Data and AI have been reshaping the way we live and work for the past few years, and the fact is that this is just the beginning. 
Everyone has been using AI-and-knowledge-infused products and services every day, sometimes in ways that may not seem obvious. One of David’s goals in this session will be to explain how these non-obvious scenarios are being powered with Knowledge and AI (and how/why, through improvements in technology, these will just get better). 

Session Keywords

Knowledge
Artificial Intelligence
Office 365
Microsoft Search

Diego Hueltes

RavenPack, Spain

Talk

Deep Learning for Lazy People... Neural Architecture Search with Automated Machine Learning

Deep Learning models are great, but choosing the right architecture is not easy. Many times, the easiest way of getting the best architecture is just by trying.
It would be nice to have a clairvoyant that is able to tell us the best architecture, right? We cannot have a clairvoyant but we have tools, like Automated Machine Learning, that are able to find the best architectures just with a few lines of code.

Session Keywords

Deep Learning
Automated Machine Learning
Machine Learning
Artificial Intelligence

Miguel Angel Fajardo

Geoblink, Spain

Talk

NewSQL: the Magic Wand of Data

New winds are blowing in the world of Data. They say there are magic systems that are capable of the impossible. Systems that guarantee the scalable performance of the NoSQLs while still maintaining the ACID transactions of relational databases. What is this kind of magic? How did it come to be? How can it be used? And more importantly, how does it work? Welcome to the world of NewSQL. Welcome to the future.

Session Keywords

NewSQL
NoSQL
Relational
Distributed

Mark Keinhoerster

codecentric AG, Germany

Tim Sabsch

codecentric AG, Germany

Talk

Practical Data Science - How to Track Your Development Process with DVC

Datacentric applications utilising machine learning models have evolved into common solutions. Many projects however still suffer from a lack of good patterns and practices, when developing such powerful technologies.

Digging down into the nitty-gritty details, we explain how you can use DVC to version all parts of your projects: From the dataset, over gluecode up to the model itself. But wait, there’s more! We show you code that covers the full development cycle, including experiments and reproducability, as well as release and deployment of your model to machines in the wild.

Session Keywords

DVC
TensorFlow
Keras

Dovydas Čeilutka

Vinted, Lithuania

Talk

(Un)ethical Artificial Intelligence: How to Keep the AI Fair for Everyone

This presentation highlights the current ethical problems that we face while building artificial intelligence solutions. The artificial intelligence systems based on machine learning algorithms are entering our products at an increasing rate. Unfortunately, keeping these systems fair is hard and a lot of hidden biases enter the models, even if the developers had the best intentions. We will investigate some of the failures of the AI systems and explore ways how to keep them fair for everyone.

Session Keywords

Data Science
Machine Learning

Andy LoPresto

Cloudera, USA

Talk

Secure IoT Command, Control, and Exfil with Apache MiNiFi

Apache MiNiFi is a lightweight application which can be deployed on hardware orders of magnitude smaller and less powerful than the existing standard data collection platforms. Not only can this data be prioritized and have some initial analysis performed at the edge, it can be encrypted and secured immediately. Local governance and regulatory policies can be applied across geopolitical boundaries to conform with legal requirements.

Session Keywords

Dataflow
IoT
Ingest
MiNiFi

Anton Tarasiuk

Legal IT Group, Ukraine

Talk

Big Data Legal Issues. GDPR and Contracts

Big Data legal issues. GDPR and contracts.
How can we use the Big Data legally?
What are the legal components of Big Data?
What about GDPR and Big Data?
Contracts on big data and for data analisys

Session Keywords

Personal data
GDPR
Contract with data scienser
Data analysis agreements

Tim Frey

iunera GmbH & Co. KG, Germany

Talk

Predicting Cryptocurrency Exchange Rates with Stream Processing, Social Data and Online Learning

In a recent project, iunera sought to determine if it is possible to predict crypto currency exchange rates by utilizing social data from Twitter. Tim will talk about their experiences and describe how they leveraged online learning in conjunction with social data to determine if they are able to predict future currency exchange rates.

Session Keywords

Big data
Data Science
Machine Learning

Maciej Marek

Philip Morris International, Poland

Talk

Data Science at PMI - The Tools of The Trade

Data Science is not a one man show. It is a team effort that requires every team member to master the tools of the trade. This is extremely important for effectively putting data science to work in a global organization. In this talk Maciej would like to share with you the best practices to start, develop and ship data science products developed inside PMI – the best practices and tools, currently in use by 40+ data scientists across four different location, where data science labs of PMI were established in 2017.

Session Keywords

CI/CD
Data Product
Reproducible research
Best Practices for Data Science