Sessions

Athan Reines

Machine Learning in a Browser

Athan Reines, Quansight

Prof. Raul Rodríguez

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

Prof. Raul Rodríguez, Woxsen School of Business

Athan Reines

Case Studies: Machine Learning in Web Applications

Athan Reines, Quansight

Jesus Rodriguez

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

Jesus Rodriguez, Invector Labs

Andreas Eberle

Playing Doom with TF-Agents and TensorFlow 2.0

Andreas Eberle, arconsis IT-Solutions GmbH

Christoph Henkelmann

Using Neural Networks for Natural Language Processing

Christoph Henkelmann, DIVISIO

Carmine Paolino

Scaling Machine Learning Systems up to Billions of Predictions per Day

Carmine Paolino, OLX Group

Jon Bratseth

Applying Machine Learning Online at Scale

Jon Bratseth, Verizon

Vadim Markovtsev

Towards a Convenient ML Infra

Vadim Markovtsev, source{d}

Burak Isikli

NLU in Other Languages

Burak Isikli, Turkcell

Oliver Zeigermann

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

Oliver Zeigermann, embarc

Juha Kiili

Asynchronous and version-controlled data science with Jupyter notebooks

Juha Kiili, Valohai

Jens Beyer

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

Jens Beyer, LAVRIO.solutions GmbH

Jesus Rodriguez

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

Jesus Rodriguez, Invector Labs

Daniel Schruhl

Christoph Windheuser

Continuous Delivery for Machine Learning Applications with Open Source Tools

Daniel Schruhl, ThoughtWorks Germany

Christoph Windheuser, ThoughtWorks Germany

Nicolas Kuhaupt

Privacy-preserving Machine Learning

Nicolas Kuhaupt, Fraunhofer IEE

Mathias Burger

Client-side Artificial Intelligence in JavaScript using Tensorflow.js

Mathias Burger, TNG Technology GmbH

Dr. Andreas Bühlmeier

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

Dr. Andreas Bühlmeier, DBC Enterprise IT Consulting

Vladimir Rybakov

Case Study: Making the Most out of a Doomed Project

Vladimir Rybakov, WaveAccess

Christoph Henkelmann

From Paper to Product – How we implemented BERT

Christoph Henkelmann, DIVISIO

Samar Singla

Speeding up Last-Mile Delivery with AI

Samar Singla, Jungleworks

Özge Sahin

Market Segmentation in the Era of Big Data

Özge Sahin, SciScry

Thomas Abend

Voice Assistants for Customer Support based on Deep Learning

Thomas Abend, VITAS.ai

Hauke Brammer

Delivering Rocketfuel – Pipelines für Deep Learning mit Small Data

Hauke Brammer, Novatec Consulting GmbH

Victoriya Kalmanovich

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

Victoriya Kalmanovich, Navy

Oleksandr Honchar

Deep Learning: the final Frontier for Time Series Analysis?

Oleksandr Honchar, Neurons Lab / Mawi Solutions

Bence Faludi

Architectures that power Machine Learning

Bence Faludi, dataleio

Dr. Danish Rafique

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

Dr. Danish Rafique, TerraLoupe GmbH

Dr. Neda Navidi

Human / AI Interaction Loop Training as a New Approach for Interactive Learning With Reinforcement-Learning Agents

Dr. Neda Navidi, AIR (AI Redefined)

Thiago de Faria

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

Thiago de Faria, LINKIT

Jan Mulkens

MLOps, Automated Machine Learning Made Easy

Jan Mulkens, Ahead with Data

Piotr Czajka

Łukasz Gebel

Machine Learning: The Bare Math Behind Libraries

Piotr Czajka, TomTom

Łukasz Gebel, TomTom

Radu Dan

On-device machine learning – Core ML vs Create ML

Radu Dan, Deloitte Digital Romania

Juantomás Garcia

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

Juantomás Garcia, Sngular People S.L

Matthias Hofmaier

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

Matthias Hofmaier, Novatec Consulting GmbH

Uri Eliabayev

AI for Decision Makers

Uri Eliabayev, Machine & Deep Learning Israel

Prof. Adam Blum

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

Prof. Adam Blum, Auger.AI

Laurent Picard

Building Smarter Solutions With No Expertise in Machine Learning

Laurent Picard, Google

Jan Mulkens

AutoML, the Good, the Bad and the Why

Jan Mulkens, Ahead with Data

Vladimir Rybakov

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

Vladimir Rybakov, WaveAccess

Prof. Debjyoti Paul

Interpretable Machine Learning – Application to Finance and Banks

Prof. Debjyoti Paul, Amazon

Michael Grogan

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

Michael Grogan, MGCodesandStats

Gunjan Dewan

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

Gunjan Dewan, Go-Jek

Dr. Luca Marchesotti

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

Dr. Luca Marchesotti, Beautifeye - Spaces

Alexey Grigorev

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

Alexey Grigorev, OLX Group

Alexander Polyakov

Protecting AI Solutions From Attacks

Alexander Polyakov, Independent Researcher

Steven Bourke

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

Steven Bourke, Outfittery

Dagmar Schuller

Next generation AI: Emotional Artificial Intelligence based on audio

Dagmar Schuller, audEERING GmbH

Christoph Henkelmann

An Introduction to Natural Language Generation

Christoph Henkelmann, DIVISIO

Hans-Peter Kuessner

Jens Polster

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

Hans-Peter Kuessner, adesso AG

Jens Polster, adesso AG

Ming Yong

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

Ming Yong, Goolge Inc

Prof. Debjyoti Paul

Multi Tasking Deep Learning for Natural Language Processing – Transfer Learning

Prof. Debjyoti Paul, Amazon

Dr. Guy Yachdav

Transforming business with AI – from vision to strategy to execution

Dr. Guy Yachdav, Artiio

Thiago da Silva Alves

Honey Bee Conservation using Deep Learning

Thiago da Silva Alves, JArchitects

Ilia Lorin

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

Ilia Lorin, MobiDev

Sergey Maximenko

“We Are Tracking You!” – Understanding Multiple Object Tracking

Sergey Maximenko, MobiDev

Maximilian Junker

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

Maximilian Junker, Qualicen

All Sessions

Athan Reines

Machine Learning in a Browser

Athan Reines, Quansight

Prof. Raul Rodríguez

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

Prof. Raul Rodríguez, Woxsen School of Business

Athan Reines

Case Studies: Machine Learning in Web Applications

Athan Reines, Quansight

Jesus Rodriguez

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

Jesus Rodriguez, Invector Labs

Andreas Eberle

Playing Doom with TF-Agents and TensorFlow 2.0

Andreas Eberle, arconsis IT-Solutions GmbH

Christoph Henkelmann

Using Neural Networks for Natural Language Processing

Christoph Henkelmann, DIVISIO

Carmine Paolino

Scaling Machine Learning Systems up to Billions of Predictions per Day

Carmine Paolino, OLX Group

Jon Bratseth

Applying Machine Learning Online at Scale

Jon Bratseth, Verizon

Vadim Markovtsev

Towards a Convenient ML Infra

Vadim Markovtsev, source{d}

Burak Isikli

NLU in Other Languages

Burak Isikli, Turkcell

Oliver Zeigermann

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

Oliver Zeigermann, embarc

Juha Kiili

Asynchronous and version-controlled data science with Jupyter notebooks

Juha Kiili, Valohai

Jens Beyer

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

Jens Beyer, LAVRIO.solutions GmbH

Jesus Rodriguez

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

Jesus Rodriguez, Invector Labs

Daniel Schruhl

Christoph Windheuser

Continuous Delivery for Machine Learning Applications with Open Source Tools

Daniel Schruhl, ThoughtWorks Germany

Christoph Windheuser, ThoughtWorks Germany

Nicolas Kuhaupt

Privacy-preserving Machine Learning

Nicolas Kuhaupt, Fraunhofer IEE

Mathias Burger

Client-side Artificial Intelligence in JavaScript using Tensorflow.js

Mathias Burger, TNG Technology GmbH

Dr. Andreas Bühlmeier

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

Dr. Andreas Bühlmeier, DBC Enterprise IT Consulting

Vladimir Rybakov

Case Study: Making the Most out of a Doomed Project

Vladimir Rybakov, WaveAccess

Christoph Henkelmann

From Paper to Product – How we implemented BERT

Christoph Henkelmann, DIVISIO

Samar Singla

Speeding up Last-Mile Delivery with AI

Samar Singla, Jungleworks

Özge Sahin

Market Segmentation in the Era of Big Data

Özge Sahin, SciScry

Thomas Abend

Voice Assistants for Customer Support based on Deep Learning

Thomas Abend, VITAS.ai

Hauke Brammer

Delivering Rocketfuel – Pipelines für Deep Learning mit Small Data

Hauke Brammer, Novatec Consulting GmbH

Victoriya Kalmanovich

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

Victoriya Kalmanovich, Navy

Oleksandr Honchar

Deep Learning: the final Frontier for Time Series Analysis?

Oleksandr Honchar, Neurons Lab / Mawi Solutions

Bence Faludi

Architectures that power Machine Learning

Bence Faludi, dataleio

Dr. Danish Rafique

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

Dr. Danish Rafique, TerraLoupe GmbH

Dr. Neda Navidi

Human / AI Interaction Loop Training as a New Approach for Interactive Learning With Reinforcement-Learning Agents

Dr. Neda Navidi, AIR (AI Redefined)

Thiago de Faria

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

Thiago de Faria, LINKIT

Jan Mulkens

MLOps, Automated Machine Learning Made Easy

Jan Mulkens, Ahead with Data

Piotr Czajka

Łukasz Gebel

Machine Learning: The Bare Math Behind Libraries

Piotr Czajka, TomTom

Łukasz Gebel, TomTom

Radu Dan

On-device machine learning – Core ML vs Create ML

Radu Dan, Deloitte Digital Romania

Juantomás Garcia

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

Juantomás Garcia, Sngular People S.L

Matthias Hofmaier

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

Matthias Hofmaier, Novatec Consulting GmbH

Uri Eliabayev

AI for Decision Makers

Uri Eliabayev, Machine & Deep Learning Israel

Prof. Adam Blum

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

Prof. Adam Blum, Auger.AI

Laurent Picard

Building Smarter Solutions With No Expertise in Machine Learning

Laurent Picard, Google

Jan Mulkens

AutoML, the Good, the Bad and the Why

Jan Mulkens, Ahead with Data

Vladimir Rybakov

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

Vladimir Rybakov, WaveAccess

Prof. Debjyoti Paul

Interpretable Machine Learning – Application to Finance and Banks

Prof. Debjyoti Paul, Amazon

Michael Grogan

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

Michael Grogan, MGCodesandStats

Gunjan Dewan

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

Gunjan Dewan, Go-Jek

Dr. Luca Marchesotti

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

Dr. Luca Marchesotti, Beautifeye - Spaces

Alexey Grigorev

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

Alexey Grigorev, OLX Group

Alexander Polyakov

Protecting AI Solutions From Attacks

Alexander Polyakov, Independent Researcher

Steven Bourke

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

Steven Bourke, Outfittery

Dagmar Schuller

Next generation AI: Emotional Artificial Intelligence based on audio

Dagmar Schuller, audEERING GmbH

Christoph Henkelmann

An Introduction to Natural Language Generation

Christoph Henkelmann, DIVISIO

Hans-Peter Kuessner

Jens Polster

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

Hans-Peter Kuessner, adesso AG

Jens Polster, adesso AG

Ming Yong

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

Ming Yong, Goolge Inc

Prof. Debjyoti Paul

Multi Tasking Deep Learning for Natural Language Processing – Transfer Learning

Prof. Debjyoti Paul, Amazon

Dr. Guy Yachdav

Transforming business with AI – from vision to strategy to execution

Dr. Guy Yachdav, Artiio

Thiago da Silva Alves

Honey Bee Conservation using Deep Learning

Thiago da Silva Alves, JArchitects

Ilia Lorin

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

Ilia Lorin, MobiDev

Sergey Maximenko

“We Are Tracking You!” – Understanding Multiple Object Tracking

Sergey Maximenko, MobiDev

Maximilian Junker

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

Maximilian Junker, Qualicen

Sessions Berlin 2019

Tue

10. Dec 2019

Wed

11. Dec 2019

10:15 - 11:00

Salon 1

Daniel Schruhl

Christoph Windheuser

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

Oleksandr Honchar

Deep Learning: the final Frontier for Time Series Analysis?

Oleksandr Honchar, Neurons Lab / Mawi Solutions

10:15 - 11:00

Salon 8+9

Thiago da Silva Alves

Honey Bee Conservation using Deep Learning

Thiago da Silva Alves, JArchitects

11:15 - 12:00

Saal A+B

Nicolas Kuhaupt

Privacy-preserving Machine Learning

Nicolas Kuhaupt, Fraunhofer IEE

11:15 - 12:00

Salon 8+9

Özge Sahin

Market Segmentation in the Era of Big Data

Özge Sahin, SciScry

14:15 - 15:00

Saal A+B

Oliver Zeigermann

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

Hans-Peter Kuessner

Jens Polster

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

Matthias Hofmaier

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

Matthias Hofmaier, Novatec Consulting GmbH

15:30 - 16:15

Salon 1

Steven Bourke

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

Steven Bourke, Outfittery

16:30 - 17:15

Saal A+B

Dagmar Schuller

Next generation AI: Emotional Artificial Intelligence based on audio

Dagmar Schuller, audEERING GmbH

Tue

10. Dec 2019

Wed

11. Dec 2019

09:00 - 09:45

Salon 1

Juha Kiili

Asynchronous and version-controlled data science with Jupyter notebooks

Juha Kiili, Valohai

09:00 - 09:45

Saal A+B

Prof. Adam Blum

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

Prof. Adam Blum, Auger.AI

10:15 - 11:00

Saal A+B

Vladimir Rybakov

Case Study: Making the Most out of a Doomed Project

Vladimir Rybakov, WaveAccess

10:15 - 11:00

Salon 6+7

Thomas Abend

Voice Assistants for Customer Support based on Deep Learning

Thomas Abend, VITAS.ai

10:15 - 11:00

Salon 8+9

Ming Yong

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

Mathias Burger

Client-side Artificial Intelligence in JavaScript using Tensorflow.js

Mathias Burger, TNG Technology GmbH

11:15 - 12:00

Salon 8+9

Alexey Grigorev

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

Alexey Grigorev, OLX Group

13:30 - 14:00

Dr. Neda Navidi

Human / AI Interaction Loop Training as a New Approach for Interactive Learning With Reinforcement-Learning Agents

Dr. Neda Navidi, AIR (AI Redefined)

14:15 - 15:00

Saal A+B

Jens Beyer

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

Jens Beyer, LAVRIO.solutions GmbH

14:15 - 15:00

Salon 8+9

Christoph Henkelmann

From Paper to Product – How we implemented BERT

Christoph Henkelmann, DIVISIO

14:15 - 15:00

Salon 1

Hauke Brammer

Delivering Rocketfuel – Pipelines für Deep Learning mit Small Data

Hauke Brammer, Novatec Consulting GmbH

15:30 - 16:15

Saal A+B

Dr. Andreas Bühlmeier

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

Dr. Andreas Bühlmeier, DBC Enterprise IT Consulting

15:30 - 16:15

Salon 8+9

Samar Singla

Speeding up Last-Mile Delivery with AI

Samar Singla, Jungleworks

Sessions Singapore 2020

Wed

09. Sep 2020

Thu

10. Sep 2020

10:00 - 10:45

Jesus Rodriguez

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

Jesus Rodriguez, Invector Labs

11:15 - 12:00

Christoph Henkelmann

Using Neural Networks for Natural Language Processing

Christoph Henkelmann, DIVISIO

14:15 - 15:00

Andreas Eberle

Playing Doom with TF-Agents and TensorFlow 2.0

Andreas Eberle, arconsis IT-Solutions GmbH

14:15 - 15:00

Burak Isikli

NLU in Other Languages

Burak Isikli, Turkcell

15:30 - 16:15

Athan Reines

Case Studies: Machine Learning in Web Applications

Athan Reines, Quansight

15:30 - 16:15

Vadim Markovtsev

Towards a Convenient ML Infra

Vadim Markovtsev, source{d}

16:30 - 17:15

Jon Bratseth

Applying Machine Learning Online at Scale

Jon Bratseth, Verizon

16:30 - 17:15

Vladimir Rybakov

09:00 - 09:45

Jesus Rodriguez

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

Jesus Rodriguez, Invector Labs

09:00 - 09:45

Victoriya Kalmanovich

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

Victoriya Kalmanovich, Navy

10:15 - 11:00

Carmine Paolino

Scaling Machine Learning Systems up to Billions of Predictions per Day

Carmine Paolino, OLX Group

11:15 - 12:00

Athan Reines

Machine Learning in a Browser

Athan Reines, Quansight

11:15 - 12:00

Prof. Debjyoti Paul

Multi Tasking Deep Learning for Natural Language Processing – Transfer Learning

Prof. Debjyoti Paul, Amazon

14:15 - 15:00

Prof. Raul Rodríguez

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

Prof. Raul Rodríguez, Woxsen School of Business

14:15 - 15:15

Samar Singla

Speeding up Last-Mile Delivery with AI

Samar Singla, Jungleworks

15:30 - 16:15

Bence Faludi

Architectures that power Machine Learning

Bence Faludi, dataleio

Sessions Munich 2020

Carmine Paolino

Scaling Machine Learning Systems up to Billions of Predictions per Day

Carmine Paolino, OLX Group

Jon Bratseth

Applying Machine Learning Online at Scale

Jon Bratseth, Verizon

Burak Isikli

NLU in Other Languages

Burak Isikli, Turkcell

Dr. Danish Rafique

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

Dr. Danish Rafique, TerraLoupe GmbH

Dr. Neda Navidi

Human / AI Interaction Loop Training as a New Approach for Interactive Learning With Reinforcement-Learning Agents

Dr. Neda Navidi, AIR (AI Redefined)

Thiago de Faria

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

Thiago de Faria, LINKIT

Jan Mulkens

MLOps, Automated Machine Learning Made Easy

Jan Mulkens, Ahead with Data

Piotr Czajka

Łukasz Gebel

Machine Learning: The Bare Math Behind Libraries

Piotr Czajka, TomTom

Łukasz Gebel, TomTom

Radu Dan

On-device machine learning – Core ML vs Create ML

Radu Dan, Deloitte Digital Romania

Juantomás Garcia

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

Juantomás Garcia, Sngular People S.L

Uri Eliabayev

AI for Decision Makers

Uri Eliabayev, Machine & Deep Learning Israel

Laurent Picard

Building Smarter Solutions With No Expertise in Machine Learning

Laurent Picard, Google

Jan Mulkens

AutoML, the Good, the Bad and the Why

Jan Mulkens, Ahead with Data

Prof. Debjyoti Paul

Interpretable Machine Learning – Application to Finance and Banks

Prof. Debjyoti Paul, Amazon

Michael Grogan

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

Michael Grogan, MGCodesandStats

Gunjan Dewan

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

Gunjan Dewan, Go-Jek

Dr. Luca Marchesotti

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

Dr. Luca Marchesotti, Beautifeye - Spaces

Alexander Polyakov

Protecting AI Solutions From Attacks

Alexander Polyakov, Independent Researcher

Christoph Henkelmann

An Introduction to Natural Language Generation

Christoph Henkelmann, DIVISIO

Dr. Guy Yachdav

Transforming business with AI – from vision to strategy to execution

Dr. Guy Yachdav, Artiio

Ilia Lorin

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

Ilia Lorin, MobiDev

Sergey Maximenko

“We Are Tracking You!” – Understanding Multiple Object Tracking

Sergey Maximenko, MobiDev

Maximilian Junker

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

Maximilian Junker, Qualicen

Sessions

ML Conference The Conference for Machine Learning Innovation

Sessions

Keynote

Session

Shorttalk

Workshop

Keynote

Session

Shorttalk

Workshop

All Sessions

Keynote

Session

Shorttalk

Workshop

Keynote

Session

Shorttalk

Workshop

Sessions Berlin 2019

Keynote

Session

Shorttalk

Workshop

Tue

ML Conference
The Conference for Machine Learning Innovation