Program

ML Summit
The big training event for Machine Learning
June 29 - July 1, 2022 | Munich

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PROGRAM ML SUMMIT 2022

Wed

29. Jun 2022
09:00 - 09:45
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Machine Learning Sucks

Dr. Pieter Buteneers, Sinch
10:00 - 13:00
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Machine Learning 101++ Using Python Part 1

Dr. Pieter Buteneers, Sinch
10:00 - 13:00
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Machine Learning 101++ Using Python Part 1

Dr. Pieter Buteneers, Sinch
10:00 - 13:00
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Deep Learning in Image and Video Applications

Dr. Majid Baa Wafaa, RecomAI
14:15 - 17:30
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Deep Learning in Image and Video Applications Part 2

Dr. Majid Baa Wafaa, RecomAI
14:15 - 17:30
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Machine Learning 101++ Using Python Part 2

Dr. Pieter Buteneers, Sinch
17:45 - 18:15
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Practical ML with Power BI Desktop

Markus Ehrenmüller-Jensen, Savory Data

Thu

30. Jun 2022
09:00 - 09:45
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How XAI will quietly revolutionize AI

Serg Masis, Syngenta
10:00 - 13:00
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Graph-Powered Machine Learning

Dr. Jörg Schad, ArangoDB
10:00 - 13:00
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Feature Engineering and feature Selection Part 1

Dr. Pieter Buteneers, Sinch
14:15 - 17:30
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Making Machine Learning Models Attack-Proof with Adversarial Robustness

Serg Masis, Syngenta
14:15 - 17:30
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Feature Engineering and feature Selection Part 2

Dr. Pieter Buteneers, Sinch
17:45 - 18:15
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Graph Analytics vs Graph ML

Dr. Jörg Schad, ArangoDB

Fri

01. Jul 2022
09:00 - 09:45
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Programming Languages for Deep Learning

Dr. Michael Sperber, Active Group
10:00 - 13:00
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How to turn large amounts of text into insights with machine learning

Dr. Christian Winkler, datanizing GmbH
10:00 - 13:00
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AI, Machine Learning & Data Science Essentials in Python Part 1

Dr. Neda Navidi, ETS
14:15 - 17:30
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AI, Machine Learning & Data Science Essentials in Python Part 2

Dr. Neda Navidi, ETS

PROGRAM ML CONFERENCE 2022

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Workshop: Machine Learning 101++ Using Python

Dr. Pieter Buteneers, Sinch
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Using A.I to make recommendations for career progression

Dorra Nouira, Boostrs
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Machine learning in the browser with TensorFlow.js

Håkan Silfvernagel, Miles Oslo AS
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Why Security is Important in ML and How to Secure your ML-based Solutions

Dr. Rachid Kherrazi, AKKA Netherlands B.V.
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Keep an eye on AI — Monitor ML models in production

Hauke Brammer, DeepUp GmbH
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Machine Learning on the Edge using TensorFlow Lite

Håkan Silfvernagel, Miles Oslo AS
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Vector embedding AI in production systems

Jon Bratseth, Yahoo
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Brains vs. Brawn – Is endless scaling really the way forward?

Christoph Henkelmann, DIVISIO
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How We Covered Concept Drifts In Time Series Forecasting For Public Transport

Dr. Tim Frey, iunera GmbH & Co. KG
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Kotlin? For Machine Learning?

Hauke Brammer, DeepUp GmbH
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Nature inspired optimization algorithms / Algorithm-based Staffing with Ant Colony Optimization

Laura Kölbl, MATHEMA GmbH
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Workshop: Advancements in Natural Language Processing (NLP)

Leonardo De Marchi, idea.io
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Greenfield and Brownfield Data Labeling – from Idea to Production with data-centric AI

Johannes Hötter, onetask.ai // kern.ai
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How AutoML can give companies, with few data scientists, a key advantage

Ioannis Tsamardinos, JADBio
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Optimize your network inference time as a data scientist, not as a web developer

Adrian Boguszewski, Intel
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Underspecified pipelines: Why good models underperform in production

Nikolay Manchev, Domino Data Lab
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IoT Analytics at Scale – Customer based product development

Danilo Dresen, taod Consulting GmbH
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Honey, I shrunk the TinyML

Lars Gregori, SAP CX
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