Data Science UA

The most complicated algorithms, revolutionary inventions, and technologies all consist of hundreds of the simplest components that use create synergy together. The ability to understand and create such projects depends on decomposition and simplification. On March 14 at the Data Science UA Conference, we will explore in details the experience of engineers, product managers, and investors in data science products.

Technology track

Data science projects workflow. Dataset optimization and solution validation, architecture and integration into existing products. Problems of education and raising expertise.

Business track

The path from problem to solution in the product. Issues of implementation and feasibility of Data Science in various fields. Difficulties in team formation, cost, and project evaluation.

Workshops track

Opportunity to get real practical insights in a short time under the guidance of leading engineers.

Panel Discussion

'Simplify the World with AI'

Feel the atmosphere of previous conferences

Technical track

Business track

Workshops

Registration

9:00 — 10:00

Conference opening

10:00 — 10:35

Oles Petriv

Reface.AI

Track opening

10:40 — 10:45

Track opening

10:40 — 10:45

17 elegant ways of shooting yourself in the foot during question-answering system development

UKR

Michael Sokolov

CTO
Dex Technologies

10:45 — 11:30

Optimization in multi-label classification and system orchestration with TFX and Kubeflow Pipelines

ENG

Mohamed-Achref Maiza

Senior Data Scientist
Renault Digital

10:45 — 11:30

Coffee break

11:30 — 11:50

Animable Neural 3D Models

UKR

Vladislav Zavadskyy

Head of Research
NeoRender

11:50 — 12:35

How we perform productive AB tests: methodology and organization of work

UKR

Alexander Shevchenko

Lead Data Analyst
Letyshops

Kostiantyn Radchenko

Product Analyst / Project Manager
Letyshops

11:50 — 12:35

Bridging Quantum Computing and Machine Learning in Tensor Flow

UKR

Mykola Maksymenko

Director of Research and Development
SoftServe

12:45 — 13:30

Top Deadly Sins of Applied Machine Learning in Finance

ENG

Dr. Luis Moreira-Matias

Head of Data Science
Kreditech

12:45 — 13:30

Creating web-app for DS stuff with Streamlit

RUS

Serhii Tiurin

Data Scientist
Data Science UA

11:40 — 13:30

Lunch

13:30 — 14:30

Challenges in hands tracking on mobile devices

RUS

Vladyslav Gorbatiuk

ML Software Engineer
Snap Inc

14:30 — 15:15

DS education

RUS

Sergey Kurson

External Relations Expert
Vodafone

14:30 — 15:15

Object tracking system using multiple NNs with an application in Sports

UKR

Raid Arfua

Senior Machine Learning Engineer
SoftConstruct

15:25 — 16:10

Data rules - the impact of Data Science on business

UKR

Yuliia Holovko

Manager, People Advisory Services
EY

Maryna Muntaniol

Senior Consultant, People Advisory Services
EY

15:25 — 16:10

Coffee break

16:10 — 16:30

Object Detection with Single Shot Networks

RUS

Andrey Nikishaev

System Architect
Moneyveo

14:30 — 16:20

ML models in production. Installation and configuration [:ua]Розгортання та налаштування продакшн пайплайнів для постійного перетренування ML моделей

UKR

Borys Pratsiuk

CTO
Scalarr

16:30 — 17:15

Automating Food Recognition for Canteens with Machine Vision

ENG

Justin Shenk

CTO
VisioLab

16:30 — 17:15

How to Identify An Object If You Must

RUS

Michael Korkin

CTO
Everguard

17:30 — 18:15

Why your state-of-the-art ML can't predict markets

RUS

Alex Honchar

Co-Founder and CTO
Neurons Lab

16:30 — 18:30

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