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MLOps community meetup #11 // Machine Learning at Scale in Mercado Libre with Carlos de la Torre

MLOps community meetup #11 // Machine Learning at Scale in Mercado Libre with Carlos de la Torre

FromMLOps.community


MLOps community meetup #11 // Machine Learning at Scale in Mercado Libre with Carlos de la Torre

FromMLOps.community

ratings:
Length:
59 minutes
Released:
May 16, 2020
Format:
Podcast episode

Description

MLOps community meetup #11 Machine Learning at scale in Mercado Libre with Carlos de la Torre  
Mercado Libre hosts the largest online commerce and payments ecosystem in Latin America. The IT department built Fury: a PaaS framework for the development and deployment of multi-cloud, multi-technology, microservices. This platform leveraged the growth of the IT area, which now counts ~4000 people.   
As such, it lacked support for machine-learning based solutions: an experimentation environment for data-scientists, infrastructure and data access support for ETL and model’s training tasks, etc.  Therefore, for over a year now, they have been developing Fury Data Apps (FDA). An extension of Fury to for the design, experimentation, development and deployment of machine-learning based solutions. It is already supporting ~500 users and some high-performance production APIs.  
In this meetup we talk about the main features of the platform, the supporting technology and why Carlos never accepted my Linkedin request.

Link to the article Carlos references: https://martinfowler.com/articles/cd4ml.html 
Join our slack community: https://join.slack.com/t/mlops-community/shared_invite/zt-391hcpnl-aSwNf_X5RyYSh40MiRe9Lw
follow us on twitter:@mlopscommunity
Sign up for the next meetup: https://zoom.us/webinar/register/WN_a_nuYR1xT86TGIB2wp9B1g  
Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/
Connect with Carlos on LinkedIn: https://www.linkedin.com/in/carlosdelatorre/
Follow Carlos on Twitter: @py_litox
Released:
May 16, 2020
Format:
Podcast episode

Titles in the series (100)

Weekly talks and fireside chats about everything that has to do with the new space emerging around DevOps for Machine Learning aka MLOps aka Machine Learning Operations.