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Kubernetes for Humans
#004 - Kubernetes For Humans Podcast with Andy McMahon (NatWest Group)
Sep 13, 2023
Andy McMahon, a data scientist and machine learning engineer, discusses his transition from data scientist to ML engineer, the challenges of implementing Kubernetes in a large organization, the future of MLOps and Kubernetes, and the enigmatic nature of Kubernetes. He also talks about successful book release and upcoming content on Kubeflow, RNNs, NLP, and generative AI.
37:21
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Quick takeaways
- The transition from data scientist to ML engineer is crucial, emphasizing the importance of engineering aspects in MLOps.
- Successful adoption of platforms like Kubeflow requires critical mass, community involvement, practical examples, and consideration of networking, security, and scalability.
Deep dives
Importance of MLOps in Financial Services
In this podcast episode, Andy McMahon, head of MLOps at a major financial services organization, highlights the significance of MLOps in their operations. The organization handles a massive volume of transactions and data, and McMahon's role is to help operationalize their data science capabilities to create value-added solutions for customers. He discusses the transition from being a data scientist to an ML engineer, emphasizing the importance of engineering aspects. McMahon also recognizes the need for data scientists to embrace the engineering side and highlights the broader industry trend of data scientists becoming ML engineers.
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