Productionizing Time-Series Workloads at Siemens Energy with Edgar Bahilo Rodriguez - #439
Analysis
This article summarizes a podcast episode from Practical AI featuring Edgar Bahilo Rodriguez, a Lead Data Scientist at Siemens Energy. The episode focuses on productionizing R workloads for machine learning, particularly within Siemens Energy's industrial applications. The discussion covers building a robust machine learning infrastructure, the use of mixed technologies, and specific applications like wind power, power production management, and environmental impact reduction. A key theme is the extensive use of time-series forecasting across these diverse use cases. The article provides a high-level overview of the conversation and directs readers to the show notes for more details.
Key Takeaways
- •Siemens Energy is productionizing R workloads for machine learning.
- •They are using mixed technologies to build machine learning models.
- •Time-series forecasting is a key application across various industrial use cases, including wind power and environmental impact reduction.
Reference
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