Speakers with real experience and valuable content applicable in practice
We have identified the most relevant topics in the field of artificial intelligence. We hope you will find something interesting for yourself.
Data Science & Machine Learning
10:00-10:45 Michael Konstantinov.
Zero Shot ’Em All
10:50-11:35 Maksym Andriushchenko.
On the Stability of Fine-Tuning BERT
11:45-12:30 Michael Yushchuk
12:35-13:20 Natalya Avanesova.
Automatic Text summarization: is GPT3 the best and only?
14:30-15:15 Fabio Petroni.
What do machines know?
15:20-16:05 Oleksiy Syvokonʹ
Transfer learning for speech processing
16:10-16:55 Nataliya Polyakovska
AI for Inventory Management in 2 months: Tips and Tricks
17:05-17:50 Vitaliy Bulygin
Object detection, segmentation and pose estimation for mobile devices
17:55-18:40 Pedro Jorge Freire
Neural network in high-speed optical fiber communications
18:45-19:30 Vlad Artemyev
AI for Business & Products
10:00-10:45 Laurent Picard.
Building smarter solutions with no expertise in machine learning
10:50-11:35 Alex Honchar.
Anti-data-science: the Taleb’s barbell in the AI world
11:45-12:30 Oleksandr Konduforov
Maximizing the profits: using ML for Dynamic Pricing problem
12:35-13:20 Volodymyr Getmanskyi
Visual mapping and navigation (Lviv SLAM)
14:30-15:15 Mykola Lavreniuk.
Using artificial intelligence methods to solve the problem of recognizing food and drinks in the canteen (KISSA AI project)
15:20-16:05 Pavlo Sakhno / Evgeniy Pahnuk
Platform of the future.
16:10-16:55 Serhiy Protsenko.
DPR – a new AI-disrupt
17:05-17:50 Oleksandr Makarevych.
Predicting Unpredictable: How to bring value to the client who doesn’t know what he wants?
17:55-18:40 Alex Mashrabov
Snapchat ML projects: overview and challenges
18:45-19:30 Alexandr Proskurin
How (not) to Apply ML in Finance: Industry use cases
Data Engineering & MLOps
10:00-10:45 Speaker’s speech canceled
10:50-11:35 Dmitrо Levin
Neural Video Watermarking
11:45-12:30 Roman Storchak
Computational Data Governance at scale.
12:35-13:20 Andrii Latysh
Practical dive into modern model monitoring
14:30-15:15 Dmytro Spodarets
How to speed up the development of ML models through MLOps
15:20-16:05 Sergiy Kamalov
Оpen source delta lake
16:10-16:55 Olga Petrova
Model-assisted data annotation
17:05-17:50 Dmitry Anoshin
Data engineering challenges at ML projects on global scale solutions
17:55-18:40 Maria Davydova
“Green” DGXs, virtual GPUs, orchestration, integration and interchangeability: how we build MLOps platform of the future.
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