Program

ML Conference 2020
The Conference for Machine Learning Innovation
November 16 – 18, 2020 | Munich

PROGRAM OF ML CONFERENCE MUNICH 2020

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Machine Learning 101++ Using Python

Dr. Pieter Buteneers, Chatlayer.ai
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Scaling Machine Learning Systems up to Billions of Predictions per Day

Carmine Paolino, OLX Group
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Applying Machine Learning Online at Scale

Jon Bratseth, Verizon
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NLU in Other Languages

Burak Isikli, Turkcell
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Production nightmare of building AI systems at scale – The last mile

Dr. Danish Rafique, TerraLoupe GmbH
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Human / AI Interaction Loop Training as a New Approach for Interactive Learning With Reinforcement-Learning Agents

Dr. Neda Navidi, AIR (AI Redefined)
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AI with a devops mindset – experimentation, sharing and easier ML deployment

Thiago de Faria, LINKIT
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MLOps, Automated Machine Learning Made Easy

Jan Mulkens, Ahead with Data
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Machine Learning: The Bare Math Behind Libraries

Piotr Czajka, TomTom
Łukasz Gebel, TomTom
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On-device machine learning – Core ML vs Create ML

Radu Dan, Deloitte Digital Romania
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AbadIA: How to build an AI from zero to learn to play and solve a tough game

Juantomás Garcia, Sngular People S.L
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AI for Decision Makers

Uri Eliabayev, Machine & Deep Learning Israel
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Data Science From Research to Production With Jupyter, Kubeflow & Nuclio

Or Zilberman, Iguazio
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Building Smarter Solutions With No Expertise in Machine Learning

Laurent Picard, Google
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Let’s Talk About Security Issues in Today’s ML Systems

David Glavas, Technical University of Munich (TUM)
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AutoML, the Good, the Bad and the Why

Jan Mulkens, Ahead with Data
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Curating Quality Datasets for Machine Learning

Jigyasa Grover, Twitter, Inc.
Rishabh Misra, Twitter, Inc.
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Back to Basics: Approaches to Machine Learning

Jigyasa Grover, Twitter, Inc.
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Interpretable Machine Learning – Application to Finance and Banks

Prof. Debjyoti Paul, Amazon
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Reinforcement Learning and Imitation Learning Workshop

Dr. Neda Navidi, AIR (AI Redefined)
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Predicting Hotel Cancellations With Machine Learning: Classification and Time Series Analysis

Michael Grogan, MGCodesandStats
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Developing a Match-Making Algorithm Between Customers and Go-Jek Products!

Gunjan Dewan, Go-Jek
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Real, Fake and Deepfake: How Deep Learning Messed up Customer (Re)Identification and How It Will Fix It

Dr. Luca Marchesotti, Beautifeye - Spaces
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Simply Ask – Natural Language Query Interface

Ayelet Arditi, Sisense
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Protecting AI Solutions From Attacks

Alexander Polyakov, Independent Researcher
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How Knowledge Graph Based Recommendations are Boosting our Natural Language Querying Engine

Dr. Yael Lev, Sisense
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An Introduction to Natural Language Generation

Christoph Henkelmann, DIVISIO
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Transforming business with AI – from vision to strategy to execution

Dr. Guy Yachdav, Artiio
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Smaller, Faster, Cheaper: CNN Optimisation Techniques in Object Detection

Ilia Lorin, MobiDev
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“We Are Tracking You!” – Understanding Multiple Object Tracking

Sergey Maximenko, MobiDev
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A Few Million Words Later – Text Analytics for Software Quality Assurance in Practice

Maximilian Junker, Qualicen
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Fraud analysis and prevention in retail with Machine Learning

Alexander Isaenco, WaveAccess RD-Software GmbH
 

ML Conference Mobile App

The ML Conference app simplifies the preparation before and during the conference:

  • People who don’t have a ticket yet, can also purchase it from the app
  • Participants get all the information on the schedule and can customize their program individually
  • All information about the speakers
  • “Information”: here you can find the location and room plan and can give feedback on the conference
  • Fast access to Twitter
  • All partners and sponsors at a glance
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