Sessions

ML Conference 2019
The Conference for Machine Learning Innovation
June 17 - 19 | Munich

DAY 1
18. Jun 2019
10:15 - 11:15
Asam 1

How do Chess Engines work? Looking at Stockfish and AlphaZero

Oliver Zeigermann, embarc
10:15 - 11:15
Cuvillies 1

Reinforcement Learning: a gentle Introduction and industrial Application

Dr. Christian Hidber, bSquare AG
10:15 - 11:15
Cuvillies 2

Embedded ML for continued Product Leadership in global Machine and Plant Construction

Peter Seeberg, asimovero.AI
11:30 - 12:30
Asam 2

The more data, the better the AI, isn’t it?

Michael Kieweg, LEVERTON GmbH
11:30 - 12:30
Cuvillies 2

Supercharging your forecasting algorithms with alternative data

Piero Ferrarese, SciScry GmbH
11:30 - 12:30
Cuvillies 1

Machine Learning Models: solving Issues in Production and beyond

Paul Dubs, Paul Dubs IT Consulting
11:30 - 12:30
Asam 1

Productionizing Machine Learning Models: Lessons learned in the Hadoop Ecosystem

Steffen Bunzel, Alexander Thamm GmbH
Simon Weiß, Alexander Thamm GmbH
14:00 - 15:00
Asam 1

Mail2Abteilung – Machine Learning in einem protected Environment

Stefan Blum, iteratec GmbH
14:00 - 15:00
Asam 2

Can UX demystify AI?

Ward Van Laer, Ixor
14:00 - 15:00
Cuvillies 2

How to implement Chatbots in an industrial Context

Dr. Christoph Windheuser, ThoughtWorks Inc.
15:30 - 16:30
Asam 2

Automated Hyperparameter Tuning

Timon Ruban, luminovo.ai
15:30 - 16:30
Cuvillies 1

Some Things I wish I had known about scaling Machine Learning Solutions

Jesus Rodriguez, Invector Labs
15:30 - 16:30
Klenze

Lebenslanges Lernen einer Maschine IoT Architekturen und Infrastruktur einer Smart Factory

Andreas Huhmann, HARTING Stiftung & Co. KG
15:30 - 16:30
Cuvillies 2

Predicting New York City Taxi demand: spatio-temporal Time Series Forecasting

Fabian Hertwig, MaibornWolff GmbH
DAY 2
19. Jun 2019
09:00 - 10:00
Cuvillies 1

Deep Learning mit Small Data

Hauke Brammer, Novatec Consulting GmbH
09:00 - 10:00
Klenze

Prevention of Claims with iot and ai.

Kai Atenhan, freeyou AG
Dominique Rondé, FreeYou AG
09:00 - 10:00
Asam 2

Deep Learning advances for Signal Processing

Oleksandr Honchar, Mawi Solutions / self-employed
09:00 - 10:00
Cuvillies 2

Unsupervised Learning with Autoencoders

Christoph Henkelmann, DIVISIO
10:30 - 11:30
Cuvillies 1

“AutoAutoML” – Towards a Standardized Automated Machine Learning Pipeline API

Adam Blum, Auger.AI
10:30 - 11:30
Asam 2

Mining Software Development History: Approaches and Challenges

Vadim Markovtsev, source{d}
11:45 - 12:45
Asam 2

Hype or Reality: Face Anti-Spoofing Solution powered by Deep Learning

Sergey Maximenko, MobiDev
11:45 - 12:45
Cuvillies 1

Evolution 3.0: Solve your everyday Problems with genetic Algorithms

Mey Beisaron, Appsflyer
11:45 - 12:45
Cuvillies 2

Honey Bee Conservation using Deep Learning

Thiago da Silva Alves, JArchitects
Jean Metz, JArchitects
15:00 - 16:00
Asam 2

Chatbots Suck

Dr. Pieter Buteneers, Chatlayer.ai
15:00 - 16:00
Cuvillies 2

Does Deep Learning make Feature Engineering obsolete?

Vladimir Rybakov, WaveAccess
15:00 - 16:00
Cuvillies 1

How we used Reinforcement Learning to solve the Abbey of Crime

Juantomás Garcia Molina, S|ngular
16:30 - 17:30
Cuvillies 2

The Data Janitor returns

Daniel Molnar, Shopify/Oberlo
16:30 - 17:30
Cuvillies 1

Deep probablistic Modelling with Pyro

Chi Nhan Nguyen, itemis