Industrializing Machine Learning at Shell with Daniel Jeavons - TWiML Talk #202
Published:Nov 21, 2018 16:32
•1 min read
•Practical AI
Analysis
This article summarizes a podcast episode featuring Daniel Jeavons, General Manager of Data Science at Shell. The discussion centers on Shell's application of machine learning (ML) within its operations. Key topics include the evolution of analytics and data science at Shell, focusing on Internet of Things (IoT) applications, edge computing, federated ML, and digital twins. The conversation also delves into the data science process at Shell and the significance of platform technologies for the company. The article highlights the practical application of ML in a large industrial setting, offering insights into challenges and strategies.
Key Takeaways
- •The article discusses the practical application of machine learning in a large industrial setting.
- •It highlights the importance of platform technologies for data science within Shell.
- •Key topics include IoT applications, edge computing, federated ML, and digital twins.
Reference
“In our conversation, we explore the evolution of analytics and data science at Shell, discussing IoT-related applications and issues, such as inference at the edge, federated ML, and digital twins, all key considerations for the way they apply ML.”