Improved Artificial Intelligence, Machine Learning and Deep Learning techniques are a breakthrough in the digital transformation
Trying to roll out these software products efficiently in production is a challenge to overcome. In this conference, we will introduce new paradigms based on good practices in DevOps development and operation.
New variants of the Ops universe; MLOps and AIOps
- These paradigms are aimed at making the model a reusable software device that can be continuously implemented and monitored via a replicable and measurable process.
- Their main benefit is that they minimise the gap between proof of concept/initial experiments and real artificial intelligence products.
- Knowledge of these techniques will help AI solution developers and architects to reliably and efficiently implement and maintain AI models and processes in production and provide analysts with a development framework to guide them.
Aimed at
- Development teams
Speaker Dr. Ana Isabel Torre Bastida
- Dr. Ana Isabel Torre Bastida, Graduate in Computer Engineering from the University of Deusto, Master’s Degree in Advanced Computer Systems and Doctor of Computer Science from the University of the Basque Country (EHU). She works at TECNALIA, mainly developing projects for customers in the energy, industrial and logistics sector through the use of Big Data technologies and AI techniques.
- Her research focuses on the pursuit of innovation by applying new Big Data technologies (data analytics and parallel computing), specifically in storage, transformation (ETL) and batch or real-time analysis/consultation, and in the roll-out phases in the production/operation of analytical processes in complex hybrid environments (Cloud/Fog/Edge Computing) to different sectors.