MLCon

The Event for Machine Learning Technologies & Innovations

ML Business & Strategy

Systems for machine learning are structured differently than conventional software systems. Developers and software architects have to rethink their approaches and break new ground. The foundation for this is a deep understanding of the potential of machine learning and what added value it can generate for your company. In the “Machine Learning Business & Strategy” track, experts present the basics of machine learning systems using practical examples to show you what you can achieve and what may not yet be possible.

Business & Strategy

Systems for machine learning are structured differently than conventional software systems. Developers and software architects have to rethink their approaches and break new ground. The foundation for this is a deep understanding of the potential of machine learning and what added value it can generate for your company. In the “Machine Learning Business & Strategy” track, experts present the basics of machine learning systems using practical examples to show you what you can achieve and what may not yet be possible.

The program of ML Conference Munich 2020 will be announced soon! As reference, please see the program of ML Conference Berlin 2019 below.

Track Speakers New York 2023

Track Speakers Singapore 2021

Dr. Tim Frey

Dr. Tim Frey

iunera GmbH & Co. KG
Sebastian Meyen

Sebastian Meyen

Software & Support Media
Zoha Rahman

Dr. Zoha Rahman

Centre For Big Data & Machine Learning
Håkan Silfvernagel

Håkan Silfvernagel

Miles Oslo AS
Dr. Raul Rodriguez

Dr. Raul Rodriguez

Woxsen University
Dr. Rachid Kherrazi

Dr. Rachid Kherrazi

AKKA Netherlands B.V.

TRACK SPEAKERS MUNICH 2024

MLCon Berlin’s program will be announced soon! For reference, please find Munich’s program.

Track Speakers Berlin 2023

Track Program New York 2023

Track Program Singapore 2021

Track Program Berlin 2023

TRACK PROGRAM MUNICH 2024

14
Feb

Google Bard: The Answer to ChatGPT?

With the release of the AI ChatGPT at the end of November 2022, OpenAI made big waves that don’t seem to be dying down. For a long time, not just in the tech bubble, people waited for the giant Google to answer. Now here it is: Google introduced its conversational AI, Bard. We take a look at the announcement, the technology, and speculate a bit about Google’s apparent hesitation.
1
Feb

ChatGPT: The Big Disruptor?

Disruptive technologies or innovations like ChatGPT set in motion a process that can change the way we do business or even, how we live. The real disruptor is not ChatGPT, but the rapid development of new technologies in the field of AI and ML that are emerging on the back of the hype around ChatGPT and OpenAI.
Product thinking is a well-known and frequently discussed approach for developing software products. The prospect of using the same approach with data, though, is new. "Data as a product" is the key phrase and one of the four pillars of the data mesh architecture concept. But what does that actually mean? How can a company develop data products for both internal and external clients? What can we learn about this from relevant SW projects? And how do agility, warehouses, and...
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Bernd Fondermann
Bernd Fondermann
Bernd Fondermann
bernd fondermann brainlounge
Welcome:MLCON Berlin 2022 starts with a full programme on several tracks. We would like to welcome you, share important information about the conference schedule and take a look at the highlights of the day. Opening Keynote:Incorporating Machine Learning into a business strategy opens up fascinating new possibilities, but is anything but simple. We have seen far too many failed ML projects or prototypes that had no impact on the business. At the same time, if ML projects are approached the...
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Christoph Henkelmann
Christoph Henkelmann
Sebastian Meyen
Sebastian Meyen
Sebastian Meyen
Software & Support Media
Christoph Windheuser
Christoph Windheuser
Biomedical Data classification with machine learning for healthcare In this study we used Biomedical data/information that relates to human health. We acquired such data for monitoring specific pathological /physiological states for the purposes of diagnosis and evaluating therapy. The data were used for decoding and eventual modeling of specific biological systems. The acquisition of the study results from the Instrumentation at the molecular/cell level, or a systemic or organ level, Medical Imaging – Mobile/portable/wearable devices – Electronic health record. Automated...
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Zoha Rahman
Dr. Zoha Rahman
Dr. Zoha Rahman
Centre For Big Data & Machine Learning
Many companies are already using machine learning and artificial intelligence algorithms. However, winning a Kaggle competition is not enough, the decisive factors are not only to train the best fitting model. The time to market of the models are crucial. To improve the time to market consistently, an end-to-end MLOps process that are required to train, test, deploy, run, and monitor ML models is essential for a company’s success. Building such a MLOps pipeline is a complex journey as the...
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Prof. Dr. René Brunner
Prof. Dr. René Brunner
Prof. Dr. René Brunner
Datamics / Professor an der Hochschule Macromedia
Eric Joachim Liese
Eric Joachim Liese
Eric Joachim Liese
BSH Home Appliances Group
Machine learning is often hyped, but how does it work? In this workshop, Dr. Pieter Buteneers will show you hands-on how you can build your own machine learning models. We will cover basic machine learning concepts such as regression, classification, over-fitting, cross-validation, and many more. After the workshop, you will go home with the basics of machine learning so you can start off on your own projects.
The ML Con Strategy Day provides a unique opportunity to learn from experts what steps must be taken to build successful ML products. It provides an in-depth overview of the approaches ML pioneers and thought leaders use to develop amazing Machine Learning implementations: which know-how is needed, which methodologies are helpful, what technology choices must be made, and how to manage ML in production. Incorporating Machine Learning into a business strategy opens up fascinating new possibilities, but is anything but...
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Christoph Henkelmann
Christoph Henkelmann
Alex Honchar
Alex Honchar
Alex Honchar
Neurons Lab
Arif Wider
Arif Wider
Arif Wider
Thoughtworks Deutschland / HTW Berlin
Christoph Windheuser
Christoph Windheuser

Behind the Tracks