Thiago de Faria is the Head of Solutions Engineering at LINKIT; a knowledge-driven organization with IT experts supporting partners with a clear path toward pain mitigation and solving business problems.
He is Passionate about data, programming and the people behind it, he has given many talks and workshops at conferences. He is sometimes on stage, coding and sometimes in meetings. Thiago loves to learn and try new things, he also likes to crack bad jokes that sound alot better in his mind. He is an active part of the community (Devopsdays Amsterdam, ITNEXT & Codemotion) and married to someone smarter than him. He is an open-source enthusiast, knowledge-sharer and a proud father.
Thiago wakes up every day with one goal: develop happy high-performing teams to decrease time-to-market and build production-ready applications always!
Experienced engineers hear about Machine Learning and AI all the time these days. They may even work in a place that has a Data Team building a prototype ML model that needs to be deployed in production ASAP – and that is just the tip of the iceberg. When do we build an ML component? When we need to find patterns without explicitly programming machines to do so. Despite not being easy to test and Data Scientists not usually having a software engineering background, ML components can drink from the same source as the DevOps movement.
This talk will introduce and give support to:
– Avoid the AI hype train
– CI/CD for ML? Yes, please, but we need to talk about Continuous evaluation!
– The ML bugs; no you cannot catch them with console.log()
– Create a safe environment for Data Scientists
– Packaging, deploying and serving ML models
By the end of this talk, engineers will further understand ML life-cycles, the AI hype and feel more comfortable supporting these types of applications.