This workshop will teach attendees how to use Azure Machine Learning for effective MLOps, addressing common challenges & improving efficiency & effectiveness of ML projects.
MLOps on Azure Machine Learning workshop is designed to provide the knowledge and share real project experience on how to effectively manage and optimize the operations of ML software using Azure Machine Learning. This workshop aims to help Data Science organizations in Azure ML adoption, as well as implementation of proper MLops practices and standards. Content of the workshop will be delivered by Senior AI Engineers with technical leadership experience in complex productization projects for large organizations. The workshop will begin with an introduction to key MLOps challenges and how they are addressed by AzureML platform, such as organization of experimentation environment, code, data and model lifecycle management, metrics tracking, production migration, monitoring, debugging, and security. The second part of the workshop is focused on Azure ML functionalities and architecture review focusing on topics like managing data, jobs, components, pipelines, environments, models, and endpoints. The workshop will conclude with walk through end-to-end example project scenario and open discussion for further questions. The agenda presented below can be tailored to meet specific needs of given organization.
Lingaro can also help in further steps of AzureML and MLOps adoption providing professional services for:
Don't miss out on this chance to gain the skills and knowledge you need to improve ML adoption and MLOps practices on Azure Machine Learning platform.