Until Conference starts: ✓ Upgrade to parallel conferences for $250 ✓ Team discount ✓ Access to devmio

Until Conference starts: ✓ Upgrade to parallel conferences for $250 ✓ Team discount ✓ Access to devmio

UNTIL OCTOBER 24: ✓ Save up to 315€ ✓ Devmio Fullstack Access ✓ Team Discount

UNTIL OCTOBER 24: ✓ Save up to 315€ ✓ Devmio Fullstack Access ✓ Team Discount

MLCON 2022 BERLIN ARCHIVE

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Machine Learning 101++ Using Python Workshop

Pieter Buteneers,
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AI-powered learning recommendation system: a map and match approach

Khieu Nguyen, Visier Inc.
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Software 2.0: How does data become an AI software artifact?

Leonard Püttmann, onetask.ai // kern.ai
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AMA (Ask Me Anything) Session

Pieter Buteneers,
Christoph Henkelmann, DIVISIO GmbH
Sebastian Meyen, Software & Support Media
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Data as a Product: How To Develop Good Data Products

Bernd Fondermann, bernd fondermann brainlounge
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Making Machine Learning Models Attack-Proof with Adversarial Robustness

Serg Masis, Syngenta
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Graph-Powered Machine Learning Workshop

Graph-Powered Machine Learning Workshop,
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Feature Engineering and feature Selection Workshop Part 2

Pieter Buteneers,
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Feature Engineering and Feature Selection Workshop Part 1

Pieter Buteneers,
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Data science without data: the cold start playbook

Alex Honchar, Neurons Lab
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Reinforcement learning and imitation learning using deep learning Workshop: Human and AI collaborations Part 1

Dr. Majid Baa Wafaa, RecomAI
Dr. Neda Navidi, ETS
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Reinforcement learning and imitation learning using deep learning Workshop: Human and AI collaborations Part 2

Dr. Majid Baa Wafaa, RecomAI
Dr. Neda Navidi, ETS
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Image Recognition with OpenCV and TensorFlow Workshop

Tim Wüllner, OPEN KNOWLEDGE GmbH
Oliver Zeigermann, OPEN KNOWLEDGE GmbH
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AI/Deep Learning in marketing and finance Applications Workshop Part 1

Dr. Majid Baa Wafaa, RecomAI
Dr. Neda Navidi, ETS
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AI/Deep Learning in marketing and finance Applications Workshop Part 2

Dr. Majid Baa Wafaa, RecomAI
Dr. Neda Navidi, ETS
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MLOps with MLFlow Workshop

Prof. Dr. René Brunner, Datamics / Professor an der Hochschule Macromedia
Saumya Goyal, Datamics GmbH
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Welcome to MLCON 2022 in Berlin and opening keynote: Machine Learning — the big picture for creating successful products

Christoph Henkelmann, DIVISIO GmbH
Sebastian Meyen, Software & Support Media
Christoph Windheuser, Databricks
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Data Centric AI vs Model Centric AI – The “right” data vs “best” model culture

Prof. Debjyoti Paul, Amazon
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Practical Experiences from setting up the complete MLOps pipeline

Prof. Dr. René Brunner, Datamics / Professor an der Hochschule Macromedia
Eric Joachim Liese, BSH Home Appliances Group
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Image Recognition: Past, Present and Future

Oliver Zeigermann, OPEN KNOWLEDGE GmbH
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MLOps – from ML model to cloud-service: challenges and pitfalls of scalable document processing

Ward Van Laer, Ixor
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So, what exactly is MLOps?

Mihailo Joksimovic, Microsoft
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Let’s learn R by debugging the Currywurst!

Mihailo Joksimovic, Microsoft
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Holistic Voice Application Monitoring: How to sleep well every night

Holistic Voice Application Monitoring: How to sleep well every night,
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Leveraging Earth Observation Satellite images for Financial Industry

Fekete Csongor, HolistiCRM Kft.
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How to write a good Training Script?

Christoph Henkelmann, DIVISIO GmbH
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Creating a testing workbench for ML teams using just Python

Darshita Chaturvedi, Atri Labs
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Machine Learning Techniques for Estimating Science and Properties of Materials

Dr. Beauty Pandey, WOXSEN University Hyderabad
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Dataset design for technically and legally clean ML development

Michael Osterrieder, vAIsual Inc
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The importance and pitfalls of pseudonymization

Lisa Becker, ML6
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How AutoML can give companies, with few data scientists, a key advantage

Ioannis Tsamardinos, JADBio
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Warning: this is not another MLOps best practices talk

Amit Bendor, Artlist
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Vector embedding AI in production systems

Jon Bratseth, Yahoo

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