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Yurii, Volodymyr, and Ruslan about MLOps and the other sexiest technologies of XXI century
๐๐ผ๐๐: Yuriy Milovanov, AI and Data Science Director, 6 years at SoftServe.
๐๐๐ฒ๐๐: Volodymyr Solskyy, Expert Data Scientist, 7 years at SoftServe.
๐๐๐ฒ๐๐: Ruslan Kusov, Infrastructure Solution Architect, 2,5 years at SoftServe.
Why the Data matter? What does the "Ops" part mean in DevOps? Why isn't Machine Learning a "rocket science" anymore? What MLOps exactly is? Let's check it out in the new episode of the podcast!
Here three of the best SoftServe experts discussed such popular directions as Big Data, Machine Learning, Artificial Intelligence, DevOps, and other kinds of "Ops." They show us the true view without pink glasses on the Data. Listen and enjoy!
๐ฌ๐ฎ:๐ฌ๐ฑ What does the booming of ML and AI mean nowadays?
๐ฌ๐ฐ:๐ญ๐ฏ Technology journeys of host and guests.
๐ญ๐ฏ:๐ฎ๐ฌ How do people usually start to implement ambitious ideas?
๐ญ๐ต:๐ฐ๐ด Why entry-level for Machine Learning become much lower.
๐ฎ๐ฒ:๐ญ๐ต How to marry technology with business expectations?
๐ฎ๐ต:๐ฐ๐ฑ What MLOps exactly is.
๐ฏ๐ฑ:๐ฑ๐ฌ How to measure the results in MLOps?
๐ฐ๐ณ:๐ฑ๐ฒ Machine Learning is all about Date, isnโt it?
๐ฑ๐ฏ:๐ฐ๐ฌ What can we expect from the future?
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By SoftServe Podcasts๐๐ผ๐๐: Yuriy Milovanov, AI and Data Science Director, 6 years at SoftServe.
๐๐๐ฒ๐๐: Volodymyr Solskyy, Expert Data Scientist, 7 years at SoftServe.
๐๐๐ฒ๐๐: Ruslan Kusov, Infrastructure Solution Architect, 2,5 years at SoftServe.
Why the Data matter? What does the "Ops" part mean in DevOps? Why isn't Machine Learning a "rocket science" anymore? What MLOps exactly is? Let's check it out in the new episode of the podcast!
Here three of the best SoftServe experts discussed such popular directions as Big Data, Machine Learning, Artificial Intelligence, DevOps, and other kinds of "Ops." They show us the true view without pink glasses on the Data. Listen and enjoy!
๐ฌ๐ฎ:๐ฌ๐ฑ What does the booming of ML and AI mean nowadays?
๐ฌ๐ฐ:๐ญ๐ฏ Technology journeys of host and guests.
๐ญ๐ฏ:๐ฎ๐ฌ How do people usually start to implement ambitious ideas?
๐ญ๐ต:๐ฐ๐ด Why entry-level for Machine Learning become much lower.
๐ฎ๐ฒ:๐ญ๐ต How to marry technology with business expectations?
๐ฎ๐ต:๐ฐ๐ฑ What MLOps exactly is.
๐ฏ๐ฑ:๐ฑ๐ฌ How to measure the results in MLOps?
๐ฐ๐ณ:๐ฑ๐ฒ Machine Learning is all about Date, isnโt it?
๐ฑ๐ฏ:๐ฐ๐ฌ What can we expect from the future?