IT Nonstop 2021

Channel: Video Archive of DataArt

Videos (54)

1 — Machine Learning - Build, Train, Deploy. And what next? MLOps to the rescue! — Konrad Lyda, DataArt
2 — Multi-model and Multi-library Deployment with MLflow - Norbert Fijalek, AI Busters
3 — To trust or not to trust AI, that is the question - Hrant Davtyan, Pinsight
4 — How to drive ROI from AI? - Hrant Davtyan, Pinsight
5 — Harnessing the virtual realm for applied AI - Alison B Lowndes, NVIDIA
6 — OCR: Research vs Production - Oles Dobosevych, Ukrainian Catholic University
7 — From One Use Case to AutoML Feature Engineering Solution - Vlad Bessmertnyy, Dmitriy Baykov, DataArt
8 — Modern State of AutoML - Eugene Kolker, Vlad Bessmertnyy, Dmitriy Baykov, DataArt
9 — Don't fail Smart Building transition: See a castle renovation&Cloud - Thavonekham Vincent, Factovia
10 — Azure Machine Learning: From Zero to Hero in 45 mins - Dmitry Soshnikov, Microsoft
11 — Simplifying industrial IoT Projects in 2 month - Ihor Leontiev, Dvigunity
12 — Anomaly Detection, Powered by Azure AI and Digital Twins - Mihail Mateev, Microsoft
13 — Deploy to Azure: What Could Possibly Go Wrong - Igor Fesenko, SoftServe
14 — Avoid mistakes building AI products - Dr Karol Przystalski, Codete
15 — Elasticsearch integrations - Martin Toshev, CoffeeCupConsulting
16 — Power BI Embedded Gen 2 Unleashed - Mihail Mateev, Microsoft
17 — Evolving role of metadata as a critical aspect of data platforms - Alexey Utkin, DataArt
18 — Elasticsearch internals - Martin Toshev, CoffeeCupConsulting
19 — Human and ML - collaboration in data labelling - Evgenii Sorokin, Toloka
20 — Keeping Pace with Data Infrastructure so it Doesn't Outrun you - Francisco Javier Arceo, FAST
21 — Model monitoring in 2021. Technics and tools - Andrii Latysh, Provectus
22 — Fine-tuning ML models to detect supermarket shelf objects from images - Mark Hamazaspyan, Pinsight
23 — How to reduce customer acquisition cost using artificial intelligence - Aryuna Merdygeeva, Starta VC
24 — Solving Traffic Signal Setting problem using graph neural networks and metaheuristics - Pawel Gora
25 — 5 things to avoid when designing OLAP cubes - Alyona Paramonova, Netology
26 — Detecting the "Fake News" Before It Was Even Written - Preslav Nakov, QCRI
27 — Leadership: A letter to my younger self - Aneta Angova, Ocado Technology
28 — The Power Of Team Dashboards As A Management Tool - Andrew Wilkinson, Ocado Technology
29 — Breaking Machine Learning Models - Ivaylo Strandjev, Hyperscience
30 — Quality evaluation of data visualization - Elizaveta Batanina, Yandex
31 — Managing the 3 Demons of Real-time Data (Cost, Scale, Latency) - Yoni Eini, Upsolver
32 — Forecasting the future: Approaches and Applications - Radostin Cholakov, AzBuki.ML / Obecto
33 — PMO Automation in Large Account - Oleksandr Romanenko, DataArt
34 — Machine Learning in Retail: Forecasting, Demand Generation, Sales Boosting - Round Table
35 — How we build the MLOps platform of tomorrow - Mariya Davydova, Neu.ro
36 — "Transactional” SQS, or how to replace a steam engine with an electric one in a moving train - Ocado
37 — From .NET to Data Engineers - Max Shevchenko, DataArt
38 — Is it a Dog or is it a Pig? Creating your own image classification app - Tomasz Stachlewski, AWS
39 — For the love of PROD: Test Your code - Darko Meszaros, AWS
40 — Introduction to Azure - Illia Chuikov, VISEO
41 — What is inside of the cloud? - Aleksandr Surkov, VISEO
42 — Building AI-based MVP using AWS - Artem Melnychenko, Wantent
43 — Data collection and processing - overview of crowdsourcing methods - Valentin Biryukov, Toloka
44 — Internals of voice assistants - Dr Stanislav Protasov, Innopolis University
45 — Work with highly loaded systems - Ivan Kostiuk, ROZETKA.
46 — To build AI, you have to think like AI - Julia Meshcheryakova, DataArt
47 — Interpretability and explainability of current ML models - Dmitry Sobolev, DataArt
48 — Tuning Hyperparameters with Reproducible Experiments - Milecia McGregor, Iterative.ai
49 — Workshop: Create your own cognitive portrait in 60 minutes
50 — Workshop: Creating Real-Time Data Streaming powered by SQL on Kubernetes
51 — Workshop: A Journey From a Single Neuron to a CNN
52 — Workshop: Themis and Transformers - teaching models to consider the context of the subject area
53 — Workshop: Training unbiased and accurate AI models
54 — Workshop: Build a CI/CD pipeline for blue/green deployments to Amazon EKS