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AI & Machine Learning for Enterprise Architects
Preparing your Interaction Arc…
OSB Coach · DigitalExpo
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1. A working mental model: ML as systems engineering with a probabilistic component. 2. The seven core concepts — training, inference, embeddings, vector search, fine-tuning, RAG, MLOps — each translated into enterprise-architecture terms. 3. A reusable Rosetta Stone glossary mapping ML vocabulary to systems vocabulary. 4. The six EA lenses (requirements, interfaces, contracts, orchestration, pipelines, governance) applied to an ML system end to end. 5. A worked example — modernizing EDI with ML — so the bridge isn't theoretical. 6. A node-by-node learning path that uses an OSB Coach to translate any new concept into the systems language you already speak.
Enterprise architects, solution architects, integration architects, senior engineers, and technical leaders who already understand systems and now have to make decisions about AI. You can read a sequence diagram, you've governed a platform, and you're tired of AI explanations pitched at people who've never shipped anything.
If you've never designed or operated a real system, the analogies in this book are bridges to nowhere — you'd be translating into a language you don't speak yet. Start with a systems foundation first. And if your goal is to publish ML research, this is the wrong book; go get the math.
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