After the essential work of the data scientist is done, models need to be trained in full data sets, evaluated, packaged up for production, and then monitored while live. The automation of these steps and of the end-to-end process - MLOPS - comes in the footsteps of DevOps, but with added complexities. This session will compare and contrast DevOps and MLOps, and demonstrate the brand new official MLOPS v2 solution accelerator that simplifies putting an AI/ML prodution solution in place with Azure Machine Machine Learning and other Azure services.
João Pedro "jota" Martins leads the Azure AI Ranger team for EMEA and Asia, a team with deep AI/ML skills focused on helping Microsoft Azure customers bring their AI workloads to Azure.
We seek to provide a respectful, friendly, professional experience for everyone, regardless of gender, sexual orientation, physical appearance, disability, age, race or religion. We do not tolerate any behavior that is harassing or degrading to any individual, in any form. The Code of Conduct will be enforced.
All live stream organizers using the Global Azure brand and Global Azure speakers are responsible for knowing and abiding by these standards. Each speaker who wishes to submit through our Call for Presentations needs to read and accept the Code of Conduct. We encourage every organizer and attendee to assist in creating a welcoming and safe environment. Live stream organizers are required to inform and enforce the Code of Conduct if they accept community content to their stream.
If you are being harassed, notice that someone else is being harassed, or have any other concerns, report it. Please report any concerns, suspicious or disruptive activity or behavior directly to any of the live stream organizers, or directly to the Global Azure admins at email@example.com. All reports to the Global admin team will remain confidential.
We expect local organizers to set up and enforce a Code of Conduct for all Global Azure live stream.
A good template can be found at https://confcodeofconduct.com/, including internationalized versions at https://github.com/confcodeofconduct/confcodeofconduct.com. An excellent version of a Code of Conduct, not a template, is built by the DDD Europe conference at https://dddeurope.com/2020/coc/.