MLOps for LLM: A Case Study on Dresscode

Short summary

MLOps tutorial walking through a 7-step pipeline (data ingestion, feature store, training, registry, deployment, monitoring, feedback loop) using Dresscode as a case study. Demonstrates practical data preprocessing for images, IoT sensors, and text with concrete examples like image compression, format standardization, and schema validation. Directly applicable patterns for building scalable AI systems.

• •7-step MLOps pipeline explained with Dresscode as real-world case study
• •Concrete preprocessing strategies for images (resizing, normalization, augmentation) and text (chunking, anonymization, normalization)
• •Cost optimization tactics like image downsampling and schema standardization for LLM inference

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