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ML BERLIN HYBRID CONFERENCE: Learn more about on-site or online attendance here

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ML BERLIN HYBRID CONFERENCE: Learn more about on-site or online attendance here

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ML SINGAPORE ONLINE CONFERENCE: Learn more about online attendance here

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ML BERLIN HYBRID CONFERENCE: Learn more about on-site or online attendance here

Program Munich

ML Conference
The Conference for Machine Learning Innovation
June 27 – 29, 2022 | Munich or Online

The program of ML Conference Munich 2022 will be announced soon! Stay tuned for more information.

Pick the program of your choice:

ML Conference Munich

Take me to the ML Munich Program

 

ML Summit

Take me to the ML Summit Program

PROGRAM OF ML CONFERENCE MUNICH 2022

All time slots are displayed in the Central European Time.
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k-NN on steroids – an introduction to approximate nearest neighbours

Kacper Łukawski, Qdrant
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Threat modeling and security assessment for ML models

Alex Polyakov, Adversa.AI
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How Machine Learning is (becoming) creative

Andreas Bühlmeier, DBC Enterprice Intelligence
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State-of-the-art in large scale recommender systems

Aditya Gulgani, Meta
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Workshop: Machine Learning 101++ Using Python

Dr. Pieter Buteneers, Sinch
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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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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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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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Dataset design for technically and legally clean ML development

Michael Osterrieder, vAIsual Inc
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The latest greatest in IoT Connectivity fuels the expansion of the IoT world

Frank Schmidt-Küntzel, Telefónica Germany
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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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Keep an eye on AI — Monitor ML models in production

Hauke Brammer, DeepUp GmbH
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Self-supervised Learning: Teaching AI common sense

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

Dorra Nouira, Boostrs
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The unreasonable effectiveness of simple models

Julien Schuermans, ML6
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IoT and Sustainability

Mirko Ross, asvin.io
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Feature Engineering and feature Selection Workshop Part 2

Dr. Pieter Buteneers, Sinch
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Welcome to the first day of the ML Con/ IoT Con and opening keynote: Brains vs. Brawn – Is endless scaling really the way forward?

Christoph Henkelmann, DIVISIO
Sebastian Meyen, Software & Support Media
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Automating inspections with smart drones

Oliver Neubauer, TOP seven GmbH & Co. KG
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Honey, I shrunk the TinyML

Lars Gregori, SAP CX
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Warning: this is not another MLOps best practices talk

Amit Bendor, Artlist
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Introduction to Sentence Embeddings

Dr. Christian Winkler, datanizing GmbH
10:30 - 11:00

Coffee Break

12:30 - 13:30

Lunch Break

15:00 - 15:30

Coffee Break

09:45 - 10:15

Coffee Break

11:00 - 11:30

Coffee Break

12:15 - 13:30

Lunch Break

14:00 - 14:30

Coffee Break

15:15 - 15:45

Coffee Break

09:45 - 10:15

Coffee Break

11:00 - 11:30

Coffee Break

12:15 - 13:30

Lunch BreaK

14:15 - 14:45

Coffee Break

15:30 - 16:00

Coffee Break

16:45 - 17:15

Coffee Break

Program ML Summit 2022