The Conference for Machine Learning Innovation

Christoph Henkelmann

Christoph Henkelmann
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Register until October 21:
✓ 50% off on all prices
✓ 10% team discount
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Join the ML Revolution!
Register until September 23:
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10 % Team Discount
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Join the ML Revolution!
Register until September 23:
✓ PS Classic or C64 Mini for free
✓ Save up to €310
10 % Team Discount
Register Now
Join the ML Revolution!
Register until the conference starts:
✓ 2-in-1 conference special
✓ 10 % Team Discount
Register Now
Join the ML Revolution!
Register until the conference starts:
✓ 2-in-1 conference special
✓ 10 % Team Discount
Register Now

Christoph Henkelmann

DIVISIO

Christoph Henkelmann holds a degree in Computer Science from the University of Bonn. He currently works at DIVISIO, an AI company from Cologne, where he is CTO and co-founder. At DIVISIO, he combines practical knowledge from two decades of server and mobile development with proven AI and ML technology. In his free time he grows cacti, practices the piano, and plays video games.

Take me to the full program of Zum vollständigen Programm von Singapore Singapore .

Take me to the full program of Zum vollständigen Programm von Berlin Berlin .

Take me to the full program of Zum vollständigen Programm von Munich Munich .

This Speaker Dieser Speaker belongs to the gehört zum Programm von SingaporeSingapore, BerlinBerlin and  und MunichMunich program. Take me to the current program of . Hier geht es zum aktuellen Programm von Singapore Singapore , Berlin Berlin or oder Munich Munich .

All talks by Christoph Henkelmann

Singapore 2021 Singapore 2021 -

An Introduction to Transformers




All talks by Christoph Henkelmann from other editions

munich 2021 munich 2021 -

Expert Panel: Natural Language Processing (NLP) — Ready for Primetime?



munich 2021 munich 2021 Berlin 2021 Berlin 2021 -

Efficient Transformers



Munich 2020 Munich 2020 online edition 2020 online edition 2020 -

An Introduction to Natural Language Generation



Singapore 2020 Singapore 2020 -

Using Neural Networks for Natural Language Processing



Berlin 2019 Berlin 2019 -

From Paper to Product – How we implemented BERT



Munich 2019 Munich 2019 -

Panel: Ask the ML Experts



Munich 2019 Munich 2019 -

TensorFlow Training on the JVM



Munich 2019 Munich 2019 munich 2021 munich 2021 -

Unsupervised Learning with Autoencoders



Berlin 2018 Berlin 2018 -

An Introduction to Clustering Algorithms



Munich 2018 Munich 2018 -

Panel: Road to Succeed – Ask the Experts



Munich 2018 Munich 2018 -

Preparing Text Input for Machine Learning



Berlin 2017 Berlin 2017 -

Enterprise Tensorflow: Running Tensorflow Models in a Java Environment



All talks by Christoph Henkelmann

munich 2021 munich 2021 Berlin 2021 Berlin 2021 -

Efficient Transformers




All talks by Christoph Henkelmann from other editions

Singapore 2021 Singapore 2021 -

An Introduction to Transformers



munich 2021 munich 2021 -

Expert Panel: Natural Language Processing (NLP) — Ready for Primetime?



Munich 2020 Munich 2020 online edition 2020 online edition 2020 -

An Introduction to Natural Language Generation



Singapore 2020 Singapore 2020 -

Using Neural Networks for Natural Language Processing



Berlin 2019 Berlin 2019 -

From Paper to Product – How we implemented BERT



Munich 2019 Munich 2019 -

Panel: Ask the ML Experts



Munich 2019 Munich 2019 -

TensorFlow Training on the JVM



Munich 2019 Munich 2019 munich 2021 munich 2021 -

Unsupervised Learning with Autoencoders



Berlin 2018 Berlin 2018 -

An Introduction to Clustering Algorithms



Munich 2018 Munich 2018 -

Panel: Road to Succeed – Ask the Experts



Munich 2018 Munich 2018 -

Preparing Text Input for Machine Learning



Berlin 2017 Berlin 2017 -

Enterprise Tensorflow: Running Tensorflow Models in a Java Environment



All talks by Christoph Henkelmann

munich 2021 munich 2021 -

Expert Panel: Natural Language Processing (NLP) — Ready for Primetime?



munich 2021 munich 2021 Berlin 2021 Berlin 2021 -

Efficient Transformers



munich 2021 munich 2021 -

Unsupervised Learning with Autoencoders




All talks by Christoph Henkelmann from other editions

Singapore 2021 Singapore 2021 -

An Introduction to Transformers



Munich 2020 Munich 2020 online edition 2020 online edition 2020 -

An Introduction to Natural Language Generation



Singapore 2020 Singapore 2020 -

Using Neural Networks for Natural Language Processing



Berlin 2019 Berlin 2019 -

From Paper to Product – How we implemented BERT



Munich 2019 Munich 2019 -

Panel: Ask the ML Experts



Munich 2019 Munich 2019 -

TensorFlow Training on the JVM



Berlin 2018 Berlin 2018 -

An Introduction to Clustering Algorithms



Munich 2018 Munich 2018 -

Panel: Road to Succeed – Ask the Experts



Munich 2018 Munich 2018 -

Preparing Text Input for Machine Learning



Berlin 2017 Berlin 2017 -

Enterprise Tensorflow: Running Tensorflow Models in a Java Environment



All talks by Christoph Henkelmann

Singapore 2021 Singapore 2021 -

An Introduction to Transformers



munich 2021 munich 2021 -

Expert Panel: Natural Language Processing (NLP) — Ready for Primetime?



munich 2021 munich 2021 Berlin 2021 Berlin 2021 -

Efficient Transformers



munich 2021 munich 2021 -

Unsupervised Learning with Autoencoders




All talks by Christoph Henkelmann from other editions

Munich 2020 Munich 2020 online edition 2020 online edition 2020 -

An Introduction to Natural Language Generation



Singapore 2020 Singapore 2020 -

Using Neural Networks for Natural Language Processing



Berlin 2019 Berlin 2019 -

From Paper to Product – How we implemented BERT



Munich 2019 Munich 2019 -

Panel: Ask the ML Experts



Munich 2019 Munich 2019 -

TensorFlow Training on the JVM



Berlin 2018 Berlin 2018 -

An Introduction to Clustering Algorithms



Munich 2018 Munich 2018 -

Panel: Road to Succeed – Ask the Experts



Munich 2018 Munich 2018 -

Preparing Text Input for Machine Learning



Berlin 2017 Berlin 2017 -

Enterprise Tensorflow: Running Tensorflow Models in a Java Environment



Behind the Tracks