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Pragmatic AI in Google Cloud

16:00 - 16:45 (GMT+02:00)
14 October 2021
Industry-Focus Session
Add to calendar 10/14/2021 16:00 10/14/2021 16:45 Europe/Bucharest Pragmatic AI in Google Cloud - BIG DATA WEEK BUCHAREST 2021 - HYBRID This session aims at offering a pragmatic approach on how AI and machine learning can be implemented in Google Cloud Platform to iteratively tackle complex business challenges, such as recommender systems, inventory optimization, order scheduling.

Speakers:
MIHAI BIZOVI, Head of Data Science @Adore Me

Click here to view more details about this session. Online hello@bigdataweek.com aKyOfPFEVzRHclXpWmTW75232

Session details

This session aims at offering a pragmatic approach on how  AI and machine learning can be implemented in Google Cloud Platform to iteratively tackle complex business challenges, such as recommender systems, inventory optimization, order scheduling.

MIHAI BIZOVI
MIHAI BIZOVI
Head of Data Science
Adore Me


Mihai describes himself as a generalist — navigating uncertainty and complexity to improve decision-making at scale with data and domain-driven software.
His work at Adore Me involves a weird mix of AI product management, decision science, and systems design.



MIHAI BIZOVI' sessions:

16:00 - 16:45 (GMT)
Oct 14, 2021
Industry-Focus Session
Add to calendar 10/14/2021 16:00 10/14/2021 16:45 Pragmatic AI in Google Cloud - BIG DATA WEEK BUCHAREST 2021 - HYBRID This session aims at offering a pragmatic approach on how AI and machine learning can be implemented in Google Cloud Platform to iteratively tackle complex business challenges, such as recommender systems, inventory optimization, order scheduling.

Speakers:
MIHAI BIZOVI, Head of Data Science @Adore Me

Click here to view more details about this session. Online hello@bigdataweek.com aKyOfPFEVzRHclXpWmTW75232

Pragmatic AI in Google Cloud

This session aims at offering a pragmatic approach on how AI and machine learning can be implemented in Google Cloud Platform to iteratively tackle complex business challenges, such as recommender systems, inventory optimization, order scheduling.


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