Training Infrastructure

Notes on Training Infrastructure for ML platform / Applied AI interview preparation. The file index below shows what's in scope; click through to the individual notes for the depth.

Interview talking points

This is a sub-topic under Fine-Tuning-Foundational-Models. See the parent for the broader interview framing.

Files in this folder

File	Title
09-training-infrastructure-mlops.md	09. Training Infrastructure and MLOps — End-to-End Fine-Tuning Pipeline
09-training_mlops_scenarios_mangaassist.md	Training MLOps Scenarios - MangaAssist
16-data-curation-synthetic-generation.md	16. Data Curation, Synthetic Generation & Active Learning — Building the Data Flywheel
16-data_curation_synthetic_generation_scenarios_mangaassist.md	Data Curation and Synthetic Generation Scenarios - MangaAssist
17-interpretability_scenarios_mangaassist.md	Interpretability Scenarios After Fine-Tuning - MangaAssist
17-visualization-and-interpretability-after-fine-tuning.md	17. Visualization and Interpretability After Fine-Tuning - Inspecting the MangaAssist Intent Classifier Beyond Accuracy
18-capstone_decision_scenarios_mangaassist.md	Capstone Decision Scenarios - MangaAssist
18-intuition-scenario.md	18. Intuition Scenario and Strategic Direction -- Meta-Learning Across Fine-Tuning Techniques

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