AI & ML
LLM Ops Impulse Talk
A comprehensive talk on deploying, monitoring, and optimizing large language models in production environments with practical examples and use cases.
Duration
2 hours + Q&A
Level
Advanced
Audience
ML Engineers, DevOps, Data Scientists
This intensive impulse talk is designed for ML engineers and DevOps professionals who need to deploy and manage large language models in production environments.
Participants will learn the entire lifecycle of LLM operations, from model selection and fine-tuning to deployment, monitoring, and optimization.
Prerequisites
- Experience with Python programming
- Basic understanding of machine learning concepts
- Initial experience with on-premise platforms and APIs (e.g., HuggingFace, Ollama, etc.)
Who Should Attend
- ML Engineers looking to operationalize LLMs
- DevOps Engineers supporting ML teams
- Technical leaders overseeing AI infrastructure
What You'll Learn
Efficiently deploy LLMs in various production environments
Fine-tune models for specific use cases
Implement proper monitoring and observability
Optimize performance and reduce operational costs
Handle model versioning and testing
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