Marian Beszedes
Innovatrics
VOL_02
23 February 2022 at 5 pm
HubHub Twin City, Bratislava & online
Do you care for Datasets as much as for code in your ML Project?
This time, we want to give you insight into how AI and machine learning methods are put to practical use at Innovatrics for training new biometric algorithms and in Swiss Re, one of the largest re-insurance companies in the world, to develop new, innovative products.
Machine learning (ML) helped us to solve such complex tasks as face recognition, however when it is done on a large scale it relies on many high-effort data management tasks. We will describe our winding road from images in folders and labels stored in CSV files to structured versioned datasets with reproducible data processing pipelines. Moreover we mention how we deal with data versioning / validation / quality evaluation, reproducible ML trainings and experiment management.
_Recording
_Speakers
Marian Beszedes, Head of Innovatrics’ R&D Center will describe the journey from images in folders and CSV files to structured versioned dataset with reproducible pipelines and statistical comparable profiles. He will also explain how we selected 3rd party tooling (dvc, gitlab, pandas, TF validation, HDF5) as well as why we have written some of the tools by ourselves. Moreover we mention our deep NN training workflow and experiment management platform (ClearML).Gutentor Simple Text
Lukas Csoka
Swiss Re
Lukas Csoka, the Head of Big Data Foundations at Swiss Re, will provide insights into how to tame really large, diverse data into producing meaningful results. Swiss Re uses these results to design new products that are innovative and dramatically different from the traditional ones — all thanks to proper use and analysis of spatial, photographic, satellite, language and other data.
_Agenda
Language: English
5:00 pm
Welcome
5:10 pm
Presentation – Do you care for Datasets as much as for code in your ML Project ? – Marian Beszedes (Innovatrics)
5:40 pm
Discussion – How Swiss Re uses AI for analyzing big data – Lukas Csoka (Swiss Re)
6:10 pm
Live Q&A – _Slido #better_ai
Past Meetups
Taming Neural Networks: Safe, Reliable and Compliant Deployment & Accuracy Improvements
While neural networks and other AI approaches are already used for many tasks in business and academia, making them compliant with the nascent AI regulations is laced with guesswork. In this instalment of Better AI Meetup, we will focus on making AI technically compliant with incoming regulations. Our main speaker, Pavol Bielik from LatticeFlow AI, will introduce LLMs’ first open-source compliance-centered evaluation framework.
In the second part of the evening, Igor Janos, head of R&D at Innovatrics, will introduce the different approaches he used to create an entirely new neural network able to accurately compare photographed fingers with rolled fingerprints for reliable identification of persons.
