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– Future of ML: Training Custom Models vs. Using Prebuilt Ones
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Classroom Contents
Elevating ML Infrastructure - Future of Machine Learning Platforms
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- 1 – Introduction: Lukas introduces Erik Bernhardsson, CEO & Founder of Modal Labs
- 2 – What Modal Labs Does and Its Vision for ML Infrastructure
- 3 – Importance of Developer Experience in Building ML Platforms
- 4 – Evolving Roles: From Data Teams to Machine Learning Engineers
- 5 – The Growing Need for GPU Access and Cloud Infrastructure
- 6 – Challenges of Scaling ML Workloads in Production
- 7 – Prioritizing Features and the Development Process at Modal
- 8 – How Modal Optimizes AI Inference and Custom Workflows
- 9 – Thinking Beyond Python: Supporting Multiple Languages in ML
- 10 – The Role of Open Source in Machine Learning Infrastructure
- 11 – Future of ML: Training Custom Models vs. Using Prebuilt Ones
- 12 – Conclusion
