Conferences / MLCon (ML Conference)
MLCON 2022 Berlin
Nov 28, 2022 – Dec 2, 2022 · Maritim proArte Hotel Berlin, Berlin, Berlin, Germany
- Conference
- MLCon (ML Conference) Data science & ML
- Dates
- Nov 28, 2022 – Dec 2, 2022
- Venue
- Maritim proArte Hotel Berlin
- Place
- Berlin, Berlin, Germany
- Format
- Hybrid
- Status
- Past
- Attendance
- —
- Website
- mlconference.ai
- Recorded
- 0 sponsors · 42 speaker appearances
- Notes
- Hybrid ('November 28 - December 2, 2022 | Berlin or online'). No sponsor list for this edition was found: the archived Berlin page still showed the Munich 2022 sponsor widget. Prices are regular list prices excluding VAT ('instead of' prices). Speakers: every program session listed for this edition in the organizer's program database (as rendered on the program/archive pages); role follows the session type (keynote/workshop/session).
Ticket prices
| Ticket | Price | Valid until | Notes | Source |
|---|---|---|---|---|
| 1-Day Pass | €719 | — | plus VAT | web.archive.org |
| 2-Day Pass | €1,129 | — | plus VAT | web.archive.org |
| 3-Day Pass | €1,339 | — | plus VAT | web.archive.org |
| 4-Day Pass | €1,759 | — | plus VAT | web.archive.org |
| 5-Day Pass | €1,969 | — | plus VAT; early-bird from EUR 1,673 incl. 10% team discount | web.archive.org |
Sponsors 0
No sponsors recorded
Speakers and talks 42
| Speaker | Company | Role | Talk | Links |
|---|---|---|---|---|
| Christoph Henkelmann | DIVISIO GmbH | Keynote | Welcome to MLCON 2022 in Berlin and opening keynote: Machine Learning — the big picture for creating successful products | — |
| Christoph Windheuser | — | Keynote | Welcome to MLCON 2022 in Berlin and opening keynote: Machine Learning — the big picture for creating successful products | — |
| Sebastian Meyen | Software & Support Media GmbH | Keynote | Welcome to MLCON 2022 in Berlin and opening keynote: Machine Learning — the big picture for creating successful products | — |
| Alex Honchar | Neurons Lab | Speaker | Data science without data: the cold start playbook | — |
| Amit Bendor | Unity | Speaker | Warning: this is not another MLOps best practices talk | — |
| Beauty Pandey | WOXSEN University Hyderabad | Speaker | Machine Learning Techniques for Estimating Science and Properties of Materials | — |
| Bernd Fondermann | algo consult | Speaker | Data as a Product: How To Develop Good Data Products | — |
| Christoph Henkelmann | DIVISIO GmbH | Speaker | How to write a good Training Script? | — |
| Christoph Henkelmann | DIVISIO GmbH | Speaker | AMA (Ask Me Anything) Session | — |
| Darshita Chaturvedi | Atri Labs | Speaker | Creating a testing workbench for ML teams using just Python | — |
| Debjyoti Paul | Amazon Web Services | Speaker | Data Centric AI vs Model Centric AI - The \"right\" data vs \"best\" model culture | — |
| Dominik Meißner | 169 Labs GmbH | Speaker | Holistic Voice Application Monitoring: How to sleep well every night | — |
| Dr. Pieter Buteneers | Emma Legal | Workshop | Feature Engineering and feature Selection Workshop Part 2 | — |
| Dr. Pieter Buteneers | Emma Legal | Workshop | Feature Engineering and Feature Selection Workshop Part 1 | — |
| Dr. Pieter Buteneers | Emma Legal | Speaker | AMA (Ask Me Anything) Session | — |
| Dr. Pieter Buteneers | Emma Legal | Workshop | Machine Learning 101++ Using Python Workshop | — |
| Eric Joachim Liese | Datics Consulting | Speaker | Practical Experiences from setting up the complete MLOps pipeline | — |
| Fekete Csongor | HolistiCRM Kft | Speaker | Leveraging Earth Observation Satellite images for Financial Industry | — |
| Ioannis Tsamardinos | JADBio | Speaker | How AutoML can give companies, with few data scientists, a key advantage | — |
| Jon Bratseth | Vespa.ai | Speaker | Vector embedding AI in production systems | — |
| Jörg Schad | ArangoDB | Workshop | Graph-Powered Machine Learning Workshop | — |
| Khieu Nguyen | Visier | Speaker | AI-powered learning recommendation system: a map and match approach | — |
| Leonard Püttmann | Kern AI | Speaker | Software 2.0: How does data become an AI software artifact? | — |
| Lisa Becker | Pure App | Speaker | The importance and pitfalls of pseudonymization | — |
| Majid Baa Wafaa | RecomAI | Workshop | AI/Deep Learning in marketing and finance Applications Workshop Part 1 | — |
| Majid Baa Wafaa | RecomAI | Workshop | AI/Deep Learning in marketing and finance Applications Workshop Part 2 | — |
| Majid Baa Wafaa | RecomAI | Workshop | Reinforcement learning and imitation learning using deep learning Workshop: Human and AI collaborations Part 1 | — |
| Majid Baa Wafaa | RecomAI | Workshop | Reinforcement learning and imitation learning using deep learning Workshop: Human and AI collaborations Part 2 | — |
| Michael Osterrieder | vAIsual Inc | Speaker | Dataset design for technically and legally clean ML development | — |
| Mihailo Joksimovic | JAGGAER | Speaker | Let's learn R by debugging the Currywurst! | — |
| Mihailo Joksimovic | JAGGAER | Speaker | So, what exactly is MLOps? | — |
| Neda Navidi | — | Workshop | AI/Deep Learning in marketing and finance Applications Workshop Part 1 | — |
| Neda Navidi | — | Workshop | AI/Deep Learning in marketing and finance Applications Workshop Part 2 | — |
| Neda Navidi | — | Workshop | Reinforcement learning and imitation learning using deep learning Workshop: Human and AI collaborations Part 1 | — |
| Neda Navidi | — | Workshop | Reinforcement learning and imitation learning using deep learning Workshop: Human and AI collaborations Part 2 | — |
| René Brunner | Datamics GmbH | Speaker | Practical Experiences from setting up the complete MLOps pipeline | — |
| René Brunner | Datamics GmbH | Workshop | MLOps with MLFlow Workshop | — |
| Saumya Goyal | Datamics GmbH | Workshop | MLOps with MLFlow Workshop | — |
| Sebastian Meyen | Software & Support Media GmbH | Speaker | AMA (Ask Me Anything) Session | — |
| Serg Masis | Syngenta | Workshop | Making Machine Learning Models Attack-Proof with Adversarial Robustness | — |
| Tim Wüllner | open knowledge | Workshop | Image Recognition with OpenCV and TensorFlow Workshop | — |
| Ward Van Laer | Ixor | Speaker | MLOps - from ML model to cloud-service: challenges and pitfalls of scalable document processing | — |