ONLY UNTIL MAY 23: ✓ Save up to 305€ ✓ Team Discount ✓ Access to devmio

ONLY UNTIL MAY 23: ✓ Save up to 305€ ✓ Team Discount ✓ Access to devmio

Limited Time offer: ✓ Save up to $950 ✓ Free ML Strategy Day ✓ Access to devmio

Limited Time offer: ✓ Save up to $950 ✓ Free ML Strategy Day ✓ Access to devmio

COMING UP NEXT: MLCon Munich | June 25 – 28, 2024

COMING UP NEXT: MLCon Munich | June 25 – 28, 2024

MLCON 2022 Munich ARCHIVE

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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

Threat modeling and security assessment for ML models,
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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

Pieter Buteneers,
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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

The latest greatest in IoT Connectivity fuels the expansion of the IoT world,
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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

Pieter Buteneers,
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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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Feature Engineering and feature Selection Part 1

Pieter Buteneers,
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How XAI will quietly revolutionize AI

Serg Masis, Syngenta
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Programming Languages for Deep Learning

Dr. Michael Sperber, Active Group
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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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The importance and pitfalls of pseudonymization

Lisa Becker, ML6
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IoT and Sustainability

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

Pieter Buteneers,
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Graph Analytics vs Graph ML

Graph Analytics vs Graph ML,
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How to turn large amounts of text into insights with machine learning

Dr. Christian Winkler, datanizing GmbH
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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 GmbH
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