Under the high patronage of his majesty the King Mohammed VI
Devoxx Morocco 2022 🇲🇦 October 4-6, Taghazout Agadir, Morocco.
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Under the high patronage of his majesty the King Mohammed VI
Devoxx Morocco 2022 🇲🇦 October 4-6, Taghazout Agadir, Morocco.

Speaker details

Marton Kodok
REEA.net

Márton is a Google Developer Expert (GDE) on Cloud, a Champion in the Cloud Innovators program, senior software architect at REEA.net who led the implementation of complex and distributed web backends serving millions of users .

Top user on top StackOverflow with over 192k reputation points (Link). Mentor and consultant for startups. Active contributor for open-source solutions like Beanstalkd console, and Riak admin interface. Expert in Cloud Technologies, Scalability, HA, Serverless, Cloud Run, Vertex AI, database systems like BigQuery, Redis, MySQL, Elasticsearch.

In recent years, one of the biggest trends in applications development has been the rise of Machine Learning solutions, tools, and managed platforms. Vertex AI is a managed unified ML platform for all your AI workloads. On the MLOps side, Vertex AI Pipelines solutions let you adopt experiment pipelining beyond the classic build, train, eval, and deploy a model. It is engineered for data scientists and data engineers, and it’s a tremendous help for those teams who don’t have DevOps or sysadmin engineers, as infrastructure management overhead has been almost completely eliminated.

Based on practical examples we will demonstrate how Vertex AI Pipelines scores high in terms of developer experience, how fits custom ML needs, and analyze results. It’s a toolset for a fully-fledged machine learning workflow, a sequence of steps in the model development, a deployment cycle, such as data preparation/validation, model training, hyperparameter tuning, model validation, and model deployment. Vertex AI comes with all standard resources plus an ML metadata store, a fully managed feature store, and a fully managed pipeline runner. 

Vertex AI Pipelines is a managed serverless toolkit, which means you don't have to fiddle with infrastructure or back-end resources to run workflows. 



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This session will deliver best practices and recommendations for tuning BI Engine for your existing BigQuery workloads for cheaper and faster queries. Learn how we at REEA are orchestrating BI Engine reservations, on a 5TB dataset, considered small for BigQuery but with big cost savings and accelerated queries. We are seeing many presentations for big enterprises, but now we are showcasing how our queries perform better with lower costs. We are going to address the top considerations when to turn on BI Engine, how to use cloud orchestration for making this an automatic process, and combined with BigQuery and Datastudio query complexity that might save precious development time, lower bills, faster queries.

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