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

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

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ML SINGAPORE - THE ONLINE CONFERENCE: Learn more about online attendance here

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

Sessions

ML Conference
The Conference for Machine Learning Innovation

Sessions

Session Type Icon

Machine Learning in a Browser

Athan Reines, Quansight
Session Type Icon

Future of HR: Implementation of RPA and AI in HR Processes Using Python and TensorFlow

Prof. Raul Rodríguez, Woxsen School of Business
Session Type Icon

Case Studies: Machine Learning in Web Applications

Athan Reines, Quansight
Session Type Icon

Doing More with Less: Building Machine Learning Solutions without Large Labeled Datasets

Jesus Rodriguez, Invector Labs
Session Type Icon

Playing Doom with TF-Agents and TensorFlow 2.0

Andreas Eberle, arconsis IT-Solutions GmbH
Session Type Icon

Using Neural Networks for Natural Language Processing

Christoph Henkelmann, DIVISIO
Session Type Icon

Scaling Machine Learning Systems up to Billions of Predictions per Day

Carmine Paolino, Alan Turing Institute
Session Type Icon

Applying Machine Learning Online at Scale

Jon Bratseth, Verizon
Session Type Icon

Towards a Convenient ML Infra

Vadim Markovtsev, source{d}
Session Type Icon

Understanding how Neural Networks work by looking at the Low Level API of TensorFlow 2

Oliver Zeigermann, embarc
Session Type Icon

Streamlining your Machine Learning Projects using MLOps with Azure Machine Learning

Sam Vanhoutte, Codit
Session Type Icon

Stopping Public Transport Coronavirus Infections with Big Data

Dr. Tim Frey, iunera GmbH & Co. KG
Session Type Icon

Asynchronous and version-controlled data science with Jupyter notebooks

Juha Kiili, Valohai
Session Type Icon

Why Security is Important in ML and How to Secure your ML-based Solutions

Dr. Rachid Kherrazi, Akka Technologies
Session Type Icon

Dockerize, Standardize, Deploy and Scale your own Machine Learning Model

Jens Beyer, LAVRIO.solutions GmbH
Session Type Icon

Leveraging Reinforcement Learning for Improvement of Traditional Controllers for a Vehicle Model – A Case Study

Christoph Stockhammer, The MathWorks GmbH
Session Type Icon

Some Things I Wish I Had Known about Scaling Machine Learning Solutions

Jesus Rodriguez, Invector Labs
Session Type Icon

Machine Learning on the Edge using TensorFlow Lite

Håkan Silfvernagel, Miles AS
Session Type Icon

Continuous Delivery for Machine Learning Applications with Open Source Tools

Daniel Schruhl, ThoughtWorks Germany
Christoph Windheuser, ThoughtWorks Germany
Session Type Icon

Pre-Moderation – The Safe Sandbox for your Community

Christian Dedié, gutefrage.net GmbH
Dr. Katsiaryna Stalpouskaya, gutefrage.net GmbH
Session Type Icon

Privacy-preserving Machine Learning

Nicolas Kuhaupt, Fraunhofer IEE
Session Type Icon

Efficient Transformers

Christoph Henkelmann, DIVISIO
Session Type Icon

Client-side Artificial Intelligence in JavaScript using Tensorflow.js

Mathias Burger, TNG Technology GmbH
Session Type Icon

Enhancing Page Visits by Topic Prediction

Dieter Jordens, Continuum Consulting NV
Session Type Icon

The Bigger the Better for NLP – or not?

Dr. Maximilian Junker, Qualicen
Session Type Icon

All You Need to Know now about (Deep) Reinforcement Learning

Dr. Andreas Bühlmeier, DBC Enterprise IT Consulting
Session Type Icon

Lean Data Science: Tailoring Agile Practices for Data Science Projects

Askhat Urazbaev, ScrumTrek
Session Type Icon

Unsupervised Category-Specific Mesh Reconstruction: A Future ML Opportunity

Thomas Chen, Academy for Mathematics, Science, and Engineering
Session Type Icon

Case Study: Making the Most out of a Doomed Project

Vladimir Rybakov, WaveAccess
Session Type Icon

Federated Learning: The Next Generation Machine Learning for Regulated Domains – Healthcare and Banking

Prof. Debjyoti Paul, Amazon
Session Type Icon

MLOps: DevOps für Machine Learning

Hauke Brammer, finpair GmbH
Session Type Icon

Algorithmic Diversity & Nonbinarity. How to Reimagine Ability, Tech & Ethics

Yonah Walker, Yonah Fund
Session Type Icon

The Missing Link: How AI can help us harness our “collective intelligence” to better societies and businesses

Kamila Hankiewicz, Untrite
Session Type Icon

From Paper to Product – How we implemented BERT

Christoph Henkelmann, DIVISIO
Session Type Icon

Speeding up Last-Mile Delivery with AI

Samar Singla, Jungleworks
Session Type Icon

Market Segmentation in the Era of Big Data

Özge Sahin, SciScry
Session Type Icon

No prejudice. No remorse. Unsupervised ML

Liudmyla Taranenko, MobiDev
Session Type Icon

Brewing Beer with the Help of IoT: Building a DIY Fermentation Sensor

Sven Haiges, SAP Hybris
Session Type Icon

IoT and eSports – Learning for the industry in your spare time

Dr. Tobias Brambach, Point 8 GmbH
Session Type Icon

Welcome & Introduction

Sebastian Meyen, Software & Support Media
Session Type Icon

Voice Assistants for Customer Support based on Deep Learning

Thomas Abend, VITAS.ai
Session Type Icon

Delivering Rocketfuel – Pipelines für Deep Learning mit Small Data

Hauke Brammer, finpair GmbH
Session Type Icon

Predictive Maintenance – How Does Data Science Revolutionize the World of Machines?

Victoriya Kalmanovich, Navy
Session Type Icon

Deep Learning: the final Frontier for Time Series Analysis?

Oleksandr Honchar, Neurons Lab / Mawi Solutions
Session Type Icon

Architectures that power Machine Learning

Bence Faludi, dataleio
Session Type Icon

Production nightmare of building AI systems at scale – The last mile

Dr. Danish Rafique, Bayer AG
Session Type Icon

Human and Multi-agent systems

Dr. Neda Navidi, École de Technologie Supérieure (ÉTS)
Session Type Icon

Natural language processing for medical data

Anja Pilz, damedic
Session Type Icon

AIoT – Die Verbindung zwischen AI und IoT beherrschen!

Laurenz Kirchner, mm1
Dr. Dirk Slama, Bosch Software Innovations
Session Type Icon

Understanding Artificial Intelligence: Explainable AI with Interpretable KPI Labels

Dr. Rudolf Felix, PSI FLS Fuzzy Logik & Neuro Systeme GmbH
Session Type Icon

AI with a devops mindset – experimentation, sharing and easier ML deployment

Thiago de Faria, LINKIT
Session Type Icon

MLOps, Automated Machine Learning Made Easy

Jan Mulkens, Ahead with Data
Session Type Icon

Machine Learning: The Bare Math Behind Libraries

Piotr Czajka, TomTom
Łukasz Gebel, TomTom
Session Type Icon

On-device machine learning – Core ML vs Create ML

Radu Dan, Deloitte Digital Romania
Session Type Icon

How We Used Machine Learning to Detect Stress among our Berlin Colleagues

Matthias Hofmaier, Novatec Consulting GmbH
Session Type Icon

AI is eating Software – how Second Generation AutoML will replace Software Development

Prof. Adam Blum, Auger.AI
Session Type Icon

Building Smarter Solutions with no Expertise in Machine Learning

Laurent Picard, Google
Session Type Icon

AutoML, the Good, the Bad and the Why

Jan Mulkens, Ahead with Data
Session Type Icon

Real Machine Learning Challenges That You’ve Never Faced at Kaggle

Vladimir Rybakov, WaveAccess
Session Type Icon

Interpretable Machine Learning – Application to Finance and Banks

Prof. Debjyoti Paul, Amazon
Session Type Icon

Predicting Hotel Cancellations With Machine Learning: Classification and Time Series Analysis

Michael Grogan, MGCodesandStats
Session Type Icon

Developing a Match-Making Algorithm Between Customers and Go-Jek Products!

Gunjan Dewan, Go-Jek
Session Type Icon

Real, Fake and Deepfake: How Deep Learning Messed up Customer (Re)Identification and How It Will Fix It

Dr. Luca Marchesotti, Beautifeye - Spaces
Session Type Icon

Automatic Image Cropping for Online Classifieds: a Journey from a Master Thesis to Production

Alexey Grigorev, OLX Group
Session Type Icon

Protecting AI Solutions From Attacks

Alex Polyakov, Adversa.AI
Session Type Icon

Building Human-in-the-Loop Machine Learning Systems – Fashion 2.0

Steven Bourke, Outfittery
Session Type Icon

Next generation AI: Emotional Artificial Intelligence based on audio

Dagmar Schuller, audEERING GmbH
Session Type Icon

How to raise intelligent Chatbots, keep them smart and make them useful

Hans-Peter Kuessner, adesso AG
Jens Polster, adesso AG
Session Type Icon

MediaPipe: Building real-time cross-platform (mobile, web, edge, desktop) Video Audio ML Pipelines

Ming Yong, Goolge Inc
Session Type Icon

Building AI startups with minimum risks

Liubov Zatolokina, MobiDev
Session Type Icon

Multi Tasking Deep Learning for Natural Language Processing – Transfer Learning

Prof. Debjyoti Paul, Amazon
Session Type Icon

Transforming Business with AI – From Vision to Strategy to Execution

Dr. Tatyana Goldberg, Allianz
Dr. Guy Yachdav, Aiola
Session Type Icon

Honey Bee Conservation using Deep Learning

Thiago da Silva Alves, JArchitects
Session Type Icon

Smaller, Faster, Cheaper: CNN Optimisation Techniques in Object Detection

Ilia Lorin, MobiDev
Session Type Icon

Real time Covid-19 detection with Audio AI

Pia Eggert, Freelancer
Session Type Icon

Unsupervised Learning with Autoencoders

Christoph Henkelmann, DIVISIO
Session Type Icon

A Few Million Words Later – Text Analytics for Software Quality Assurance in Practice

Dr. Maximilian Junker, Qualicen
Session Type Icon

NLU in Other Languages

Burak Isikli, Akbank
Session Type Icon

Satellite imagery analysis: Machine Learning to prevent environmental crisis

Vladimir Rybakov, WaveAccess
Session Type Icon

AbadIA: How to build an AI from zero to learn to play and solve a tough game

Juantomás Garcia, Sngular People S.L
Session Type Icon

An Introduction to Natural Language Generation

Christoph Henkelmann, DIVISIO
Session Type Icon

Fast and accurate: AI-based video processing

Sergey Maximenko, MobiDev

All Sessions

Session Type Icon

Machine Learning in a Browser

Athan Reines, Quansight
Session Type Icon

Future of HR: Implementation of RPA and AI in HR Processes Using Python and TensorFlow

Prof. Raul Rodríguez, Woxsen School of Business
Session Type Icon

Case Studies: Machine Learning in Web Applications

Athan Reines, Quansight
Session Type Icon

Doing More with Less: Building Machine Learning Solutions without Large Labeled Datasets

Jesus Rodriguez, Invector Labs
Session Type Icon

Playing Doom with TF-Agents and TensorFlow 2.0

Andreas Eberle, arconsis IT-Solutions GmbH
Session Type Icon

Using Neural Networks for Natural Language Processing

Christoph Henkelmann, DIVISIO
Session Type Icon

Scaling Machine Learning Systems up to Billions of Predictions per Day

Carmine Paolino, Alan Turing Institute
Session Type Icon

Applying Machine Learning Online at Scale

Jon Bratseth, Verizon
Session Type Icon

Towards a Convenient ML Infra

Vadim Markovtsev, source{d}
Session Type Icon

Understanding how Neural Networks work by looking at the Low Level API of TensorFlow 2

Oliver Zeigermann, embarc
Session Type Icon

Streamlining your Machine Learning Projects using MLOps with Azure Machine Learning

Sam Vanhoutte, Codit
Session Type Icon

Stopping Public Transport Coronavirus Infections with Big Data

Dr. Tim Frey, iunera GmbH & Co. KG
Session Type Icon

Asynchronous and version-controlled data science with Jupyter notebooks

Juha Kiili, Valohai
Session Type Icon

Why Security is Important in ML and How to Secure your ML-based Solutions

Dr. Rachid Kherrazi, Akka Technologies
Session Type Icon

Dockerize, Standardize, Deploy and Scale your own Machine Learning Model

Jens Beyer, LAVRIO.solutions GmbH
Session Type Icon

Leveraging Reinforcement Learning for Improvement of Traditional Controllers for a Vehicle Model – A Case Study

Christoph Stockhammer, The MathWorks GmbH
Session Type Icon

Some Things I Wish I Had Known about Scaling Machine Learning Solutions

Jesus Rodriguez, Invector Labs
Session Type Icon

Machine Learning on the Edge using TensorFlow Lite

Håkan Silfvernagel, Miles AS
Session Type Icon

Continuous Delivery for Machine Learning Applications with Open Source Tools

Daniel Schruhl, ThoughtWorks Germany
Christoph Windheuser, ThoughtWorks Germany
Session Type Icon

Pre-Moderation – The Safe Sandbox for your Community

Christian Dedié, gutefrage.net GmbH
Dr. Katsiaryna Stalpouskaya, gutefrage.net GmbH
Session Type Icon

Privacy-preserving Machine Learning

Nicolas Kuhaupt, Fraunhofer IEE
Session Type Icon

Efficient Transformers

Christoph Henkelmann, DIVISIO
Session Type Icon

Client-side Artificial Intelligence in JavaScript using Tensorflow.js

Mathias Burger, TNG Technology GmbH
Session Type Icon

Enhancing Page Visits by Topic Prediction

Dieter Jordens, Continuum Consulting NV
Session Type Icon

The Bigger the Better for NLP – or not?

Dr. Maximilian Junker, Qualicen
Session Type Icon

All You Need to Know now about (Deep) Reinforcement Learning

Dr. Andreas Bühlmeier, DBC Enterprise IT Consulting
Session Type Icon

Lean Data Science: Tailoring Agile Practices for Data Science Projects

Askhat Urazbaev, ScrumTrek
Session Type Icon

Unsupervised Category-Specific Mesh Reconstruction: A Future ML Opportunity

Thomas Chen, Academy for Mathematics, Science, and Engineering
Session Type Icon

Case Study: Making the Most out of a Doomed Project

Vladimir Rybakov, WaveAccess
Session Type Icon

Federated Learning: The Next Generation Machine Learning for Regulated Domains – Healthcare and Banking

Prof. Debjyoti Paul, Amazon
Session Type Icon

MLOps: DevOps für Machine Learning

Hauke Brammer, finpair GmbH
Session Type Icon

Algorithmic Diversity & Nonbinarity. How to Reimagine Ability, Tech & Ethics

Yonah Walker, Yonah Fund
Session Type Icon

The Missing Link: How AI can help us harness our “collective intelligence” to better societies and businesses

Kamila Hankiewicz, Untrite
Session Type Icon

From Paper to Product – How we implemented BERT

Christoph Henkelmann, DIVISIO
Session Type Icon

Speeding up Last-Mile Delivery with AI

Samar Singla, Jungleworks
Session Type Icon

Market Segmentation in the Era of Big Data

Özge Sahin, SciScry
Session Type Icon

No prejudice. No remorse. Unsupervised ML

Liudmyla Taranenko, MobiDev
Session Type Icon

Brewing Beer with the Help of IoT: Building a DIY Fermentation Sensor

Sven Haiges, SAP Hybris
Session Type Icon

IoT and eSports – Learning for the industry in your spare time

Dr. Tobias Brambach, Point 8 GmbH
Session Type Icon

Welcome & Introduction

Sebastian Meyen, Software & Support Media
Session Type Icon

Voice Assistants for Customer Support based on Deep Learning

Thomas Abend, VITAS.ai
Session Type Icon

Delivering Rocketfuel – Pipelines für Deep Learning mit Small Data

Hauke Brammer, finpair GmbH
Session Type Icon

Predictive Maintenance – How Does Data Science Revolutionize the World of Machines?

Victoriya Kalmanovich, Navy
Session Type Icon

Deep Learning: the final Frontier for Time Series Analysis?

Oleksandr Honchar, Neurons Lab / Mawi Solutions
Session Type Icon

Architectures that power Machine Learning

Bence Faludi, dataleio
Session Type Icon

Production nightmare of building AI systems at scale – The last mile

Dr. Danish Rafique, Bayer AG
Session Type Icon

Human and Multi-agent systems

Dr. Neda Navidi, École de Technologie Supérieure (ÉTS)
Session Type Icon

Natural language processing for medical data

Anja Pilz, damedic
Session Type Icon

AIoT – Die Verbindung zwischen AI und IoT beherrschen!

Laurenz Kirchner, mm1
Dr. Dirk Slama, Bosch Software Innovations
Session Type Icon

Understanding Artificial Intelligence: Explainable AI with Interpretable KPI Labels

Dr. Rudolf Felix, PSI FLS Fuzzy Logik & Neuro Systeme GmbH
Session Type Icon

AI with a devops mindset – experimentation, sharing and easier ML deployment

Thiago de Faria, LINKIT
Session Type Icon

MLOps, Automated Machine Learning Made Easy

Jan Mulkens, Ahead with Data
Session Type Icon

Machine Learning: The Bare Math Behind Libraries

Piotr Czajka, TomTom
Łukasz Gebel, TomTom
Session Type Icon

On-device machine learning – Core ML vs Create ML

Radu Dan, Deloitte Digital Romania
Session Type Icon

How We Used Machine Learning to Detect Stress among our Berlin Colleagues

Matthias Hofmaier, Novatec Consulting GmbH
Session Type Icon

AI is eating Software – how Second Generation AutoML will replace Software Development

Prof. Adam Blum, Auger.AI
Session Type Icon

Building Smarter Solutions with no Expertise in Machine Learning

Laurent Picard, Google
Session Type Icon

AutoML, the Good, the Bad and the Why

Jan Mulkens, Ahead with Data
Session Type Icon

Real Machine Learning Challenges That You’ve Never Faced at Kaggle

Vladimir Rybakov, WaveAccess
Session Type Icon

Interpretable Machine Learning – Application to Finance and Banks

Prof. Debjyoti Paul, Amazon
Session Type Icon

Predicting Hotel Cancellations With Machine Learning: Classification and Time Series Analysis

Michael Grogan, MGCodesandStats
Session Type Icon

Developing a Match-Making Algorithm Between Customers and Go-Jek Products!

Gunjan Dewan, Go-Jek
Session Type Icon

Real, Fake and Deepfake: How Deep Learning Messed up Customer (Re)Identification and How It Will Fix It

Dr. Luca Marchesotti, Beautifeye - Spaces
Session Type Icon

Automatic Image Cropping for Online Classifieds: a Journey from a Master Thesis to Production

Alexey Grigorev, OLX Group
Session Type Icon

Protecting AI Solutions From Attacks

Alex Polyakov, Adversa.AI
Session Type Icon

Building Human-in-the-Loop Machine Learning Systems – Fashion 2.0

Steven Bourke, Outfittery
Session Type Icon

Next generation AI: Emotional Artificial Intelligence based on audio

Dagmar Schuller, audEERING GmbH
Session Type Icon

How to raise intelligent Chatbots, keep them smart and make them useful

Hans-Peter Kuessner, adesso AG
Jens Polster, adesso AG
Session Type Icon

MediaPipe: Building real-time cross-platform (mobile, web, edge, desktop) Video Audio ML Pipelines

Ming Yong, Goolge Inc
Session Type Icon

Building AI startups with minimum risks

Liubov Zatolokina, MobiDev
Session Type Icon

Multi Tasking Deep Learning for Natural Language Processing – Transfer Learning

Prof. Debjyoti Paul, Amazon
Session Type Icon

Transforming Business with AI – From Vision to Strategy to Execution

Dr. Tatyana Goldberg, Allianz
Dr. Guy Yachdav, Aiola
Session Type Icon

Honey Bee Conservation using Deep Learning

Thiago da Silva Alves, JArchitects
Session Type Icon

Smaller, Faster, Cheaper: CNN Optimisation Techniques in Object Detection

Ilia Lorin, MobiDev
Session Type Icon

Real time Covid-19 detection with Audio AI

Pia Eggert, Freelancer
Session Type Icon

Unsupervised Learning with Autoencoders

Christoph Henkelmann, DIVISIO
Session Type Icon

A Few Million Words Later – Text Analytics for Software Quality Assurance in Practice

Dr. Maximilian Junker, Qualicen
Session Type Icon

NLU in Other Languages

Burak Isikli, Akbank
Session Type Icon

Satellite imagery analysis: Machine Learning to prevent environmental crisis

Vladimir Rybakov, WaveAccess
Session Type Icon

AbadIA: How to build an AI from zero to learn to play and solve a tough game

Juantomás Garcia, Sngular People S.L
Session Type Icon

An Introduction to Natural Language Generation

Christoph Henkelmann, DIVISIO
Session Type Icon

Fast and accurate: AI-based video processing

Sergey Maximenko, MobiDev

Sessions Berlin 2019

Tue

10. Dec 2019
10:15 - 11:00
Salon 1
Session Type Icon

Continuous Delivery for Machine Learning Applications with Open Source Tools

Daniel Schruhl, ThoughtWorks Germany
Christoph Windheuser, ThoughtWorks Germany
10:15 - 11:00
Saal A+B
Session Type Icon

Deep Learning: the final Frontier for Time Series Analysis?

Oleksandr Honchar, Neurons Lab / Mawi Solutions
10:15 - 11:00
Salon 8+9
Session Type Icon

Honey Bee Conservation using Deep Learning

Thiago da Silva Alves, JArchitects
11:15 - 12:00
Saal A+B
Session Type Icon

Privacy-preserving Machine Learning

Nicolas Kuhaupt, Fraunhofer IEE
11:15 - 12:00
Salon 8+9
Session Type Icon

Market Segmentation in the Era of Big Data

Özge Sahin, SciScry
14:15 - 15:00
Saal A+B
Session Type Icon

Understanding how Neural Networks work by looking at the Low Level API of TensorFlow 2

Oliver Zeigermann, embarc
14:15 - 15:00
Salon 8+9
Session Type Icon

How to raise intelligent Chatbots, keep them smart and make them useful

Hans-Peter Kuessner, adesso AG
Jens Polster, adesso AG
15:30 - 16:15
Salon 8+9
Session Type Icon

How We Used Machine Learning to Detect Stress among our Berlin Colleagues

Matthias Hofmaier, Novatec Consulting GmbH
15:30 - 16:15
Salon 1
Session Type Icon

Building Human-in-the-Loop Machine Learning Systems – Fashion 2.0

Steven Bourke, Outfittery
16:30 - 17:15
Saal A+B
Session Type Icon

Next generation AI: Emotional Artificial Intelligence based on audio

Dagmar Schuller, audEERING GmbH

Wed

11. Dec 2019
09:00 - 09:45
Salon 1
Session Type Icon

Asynchronous and version-controlled data science with Jupyter notebooks

Juha Kiili, Valohai
09:00 - 09:45
Saal A+B
Session Type Icon

AI is eating Software – how Second Generation AutoML will replace Software Development

Prof. Adam Blum, Auger.AI
10:15 - 11:00
Saal A+B
Session Type Icon

Case Study: Making the Most out of a Doomed Project

Vladimir Rybakov, WaveAccess
10:15 - 11:00
Salon 6+7
Session Type Icon

Voice Assistants for Customer Support based on Deep Learning

Thomas Abend, VITAS.ai
10:15 - 11:00
Salon 8+9
Session Type Icon

MediaPipe: Building real-time cross-platform (mobile, web, edge, desktop) Video Audio ML Pipelines

Ming Yong, Goolge Inc
11:15 - 12:00
Saal A+B
Session Type Icon

Client-side Artificial Intelligence in JavaScript using Tensorflow.js

Mathias Burger, TNG Technology GmbH
11:15 - 12:00
Salon 8+9
Session Type Icon

Automatic Image Cropping for Online Classifieds: a Journey from a Master Thesis to Production

Alexey Grigorev, OLX Group
13:30 - 14:00
Session Type Icon

Human and Multi-agent systems

Dr. Neda Navidi, École de Technologie Supérieure (ÉTS)
14:15 - 15:00
Saal A+B
Session Type Icon

Dockerize, Standardize, Deploy and Scale your own Machine Learning Model

Jens Beyer, LAVRIO.solutions GmbH
14:15 - 15:00
Salon 8+9
Session Type Icon

From Paper to Product – How we implemented BERT

Christoph Henkelmann, DIVISIO
14:15 - 15:00
Salon 1
Session Type Icon

Delivering Rocketfuel – Pipelines für Deep Learning mit Small Data

Hauke Brammer, finpair GmbH
15:30 - 16:15
Saal A+B
Session Type Icon

All You Need to Know now about (Deep) Reinforcement Learning

Dr. Andreas Bühlmeier, DBC Enterprise IT Consulting
15:30 - 16:15
Salon 8+9
Session Type Icon

Speeding up Last-Mile Delivery with AI

Samar Singla, Jungleworks

The sessions of ML Conference Singapore 2021 will be announced soon! Stay tuned for more information.

Sessions Singapore 2020

Sessions Munich 2021

Tue

22. Jun 2021
10:00 - 10:45
Session Type Icon

The Missing Link: How AI can help us harness our “collective intelligence” to better societies and businesses

Kamila Hankiewicz, Untrite
11:15 - 12:00
Session Type Icon

Lean Data Science: Tailoring Agile Practices for Data Science Projects

Askhat Urazbaev, ScrumTrek
11:15 - 12:00
Session Type Icon

Algorithmic Diversity & Nonbinarity. How to Reimagine Ability, Tech & Ethics

Yonah Walker, Yonah Fund
12:15 - 13:00
Session Type Icon

Federated Learning: The Next Generation Machine Learning for Regulated Domains – Healthcare and Banking

Prof. Debjyoti Paul, Amazon
14:45 - 15:30
Session Type Icon

Why Security is Important in ML and How to Secure your ML-based Solutions

Dr. Rachid Kherrazi, Akka Technologies
14:45 - 15:30
Session Type Icon

Pre-Moderation – The Safe Sandbox for your Community

Christian Dedié, gutefrage.net GmbH
Dr. Katsiaryna Stalpouskaya, gutefrage.net GmbH
16:00 - 16:45
Session Type Icon

Machine Learning on the Edge using TensorFlow Lite

Håkan Silfvernagel, Miles AS
16:00 - 16:45
Session Type Icon

Natural language processing for medical data

Anja Pilz, damedic
17:00 - 17:45
Session Type Icon

Unsupervised Category-Specific Mesh Reconstruction: A Future ML Opportunity

Thomas Chen, Academy for Mathematics, Science, and Engineering
17:00 - 17:45
Session Type Icon

IoT and eSports – Learning for the industry in your spare time

Dr. Tobias Brambach, Point 8 GmbH
17:00 - 17:45
Session Type Icon

Transforming Business with AI – From Vision to Strategy to Execution

Dr. Tatyana Goldberg, Allianz
Dr. Guy Yachdav, Aiola

Wed

23. Jun 2021
09:15 - 10:00
Session Type Icon

Enhancing Page Visits by Topic Prediction

Dieter Jordens, Continuum Consulting NV
09:15 - 10:00
Session Type Icon

Unsupervised Learning with Autoencoders

Christoph Henkelmann, DIVISIO
10:15 - 11:00
Session Type Icon

Efficient Transformers

Christoph Henkelmann, DIVISIO
10:15 - 11:00
Session Type Icon

The Bigger the Better for NLP – or not?

Dr. Maximilian Junker, Qualicen
11:30 - 12:15
Session Type Icon

Stopping Public Transport Coronavirus Infections with Big Data

Dr. Tim Frey, iunera GmbH & Co. KG
11:30 - 12:15
Session Type Icon

Brewing Beer with the Help of IoT: Building a DIY Fermentation Sensor

Sven Haiges, SAP Hybris
11:30 - 12:15
Session Type Icon

Understanding Artificial Intelligence: Explainable AI with Interpretable KPI Labels

Dr. Rudolf Felix, PSI FLS Fuzzy Logik & Neuro Systeme GmbH
14:00 - 14:45
Session Type Icon

Leveraging Reinforcement Learning for Improvement of Traditional Controllers for a Vehicle Model – A Case Study

Christoph Stockhammer, The MathWorks GmbH
14:00 - 14:45
Session Type Icon

MLOps: DevOps für Machine Learning

Hauke Brammer, finpair GmbH
15:15 - 16:00
Session Type Icon

Streamlining your Machine Learning Projects using MLOps with Azure Machine Learning

Sam Vanhoutte, Codit
15:15 - 16:00
Session Type Icon

Machine Learning: The Bare Math Behind Libraries

Piotr Czajka, TomTom
Łukasz Gebel, TomTom
16:15 - 17:00
Session Type Icon

AIoT – Die Verbindung zwischen AI und IoT beherrschen!

Laurenz Kirchner, mm1
Dr. Dirk Slama, Bosch Software Innovations
16:15 - 17:00
Session Type Icon

Building Smarter Solutions with no Expertise in Machine Learning

Laurent Picard, Google

The sessions of ML Conference Munich 2021 will be announced soon! Stay tuned for more information.