“Moritz is a Senior Cloud Solutions Architect in AI at Microsoft with a long term focus on AI/ML, AI Business Development and Strategy, DW/BI and Analytics + Data Platform. In particular, he specializes in NLP, Cognitive Services, Forecasting, and AI Automation across Supply Chain, Healthcare, Finance and Insurance. As a Principal Data Scientist and Data Professional, his big passion is to revolutionize high-risk industries with innovative deep machine intelligence, deliver high scalable customer-centric solutions, transforming data into actions, and enabling the AI-driven enterprise. Outside of Microsoft, Moritz supports a NLP Healthcare company and is a career advisor for AI/ML at Harvard University.
Moritz earned his Masters Degree in Information Management Systems from Harvard University, Stanford’s Artificial Intelligence Professional Certificate, and several industry/solution certifications.”
May 26, 2021 03:15 PM PT
Supply Chain, Healthcare, Insurance, and Finance often require highly accurate forecasting models in an enterprise large-scale fashion. With Azure Machine Learning on Azure Databricks, the scale and speed to large-scale many-models can be achieved and time-to-product decreases drastically. The better-together story poses an enterprise approach to AI/ML.
Azure AutoML offers an elegant solution efficiently to build forecasting models on Azure Databricks compute solving sophisticated business problems. The presentation covers the Azure Machine Learning + Azure Databricks approach (see slides attached) while the demo covers a hands-on business problem building a forecasting model in Azure Databricks using Azure Machine Learning. The AI/ML better-together story is elevated as MLFlow for Data Science Lifecycle Management and Hyperopt for distributed model execution completes AI/ML enterprise readiness for industry problems.