AI Solution Architecture Masterclass Ep5 – Intelligence Layer (Model Selection & Fine-Tuning) скачать в хорошем качестве

AI Solution Architecture Masterclass Ep5 – Intelligence Layer (Model Selection & Fine-Tuning)

This video is part of the AI Solution Architecture Masterclass series. Watch the full playlist to understand how enterprise AI systems are designed end-to-end. 📌 Full AI Solution Architecture Playlist:    • AI Solution Architecture Masterclass — Fro...   📚 Start the course here: 1. AI Solution Architecture: Masterclass The 6-Layer Framework for Production AI    • AI Solution Architecture Masterclass – The...   The first one is me introducing the playlist 2.AI Solution Architecture Masterclass Ep1 – The 6 Core Layers Explained (From Demo to Production)    • AI Solution Architecture Masterclass Ep1 –...   In this video, we explore the Intelligence Layer, the core component responsible for model selection, fine-tuning, evaluation, and governance of AI systems. The Intelligence Layer determines the cost, performance, and reliability of enterprise AI applications. Choosing the right model and evaluation framework can mean the difference between a scalable AI platform and an expensive experimental system. In this episode we cover: • Why LLM model selection determines cost, quality, and operational control • The trade-offs between proprietary models (GPT-4, Claude) and open-source models (Llama, Mixtral) • When to use prompt engineering vs LoRA vs full fine-tuning • How to design model versioning and registry strategies for production AI • The evaluation framework used to measure model performance before deployment • Production metrics such as F1 score, hallucination rate, latency, and throughput • Responsible AI practices including deployment controls, monitoring, and rollback mechanisms You will also learn how enterprise teams design LLM governance frameworks, including canary deployment, drift detection, and automated rollback policies. This episode is part of the Enterprise AI Solution Architecture series, where we break down the layers required to build production-grade AI systems. AI Solution Architecture Layers Infrastructure Layer Intelligence Layer Knowledge Layer Agentic Layer Protection Layer LLMOps & GenAIOps Design Principles AI Architecture Series This video is part of the AI Solution Architecture Masterclass where we cover: AI Architecture Foundations Data & Knowledge Layer Intelligence Layer (this episode) Orchestration Layer Safety & Guardrails AI Application Layer Subscribe for More If you want to learn how to build enterprise-grade AI platforms, subscribe for upcoming episodes covering: • RAG Architecture • Agentic AI Systems • AI Governance & Safety • LLM Infrastructure Design • Enterprise AI Deployment Patterns Ahmed Mahmoud Principal Data Engineer | Founder – DataMindAI Email: amahmoud@datamindaiwithahmed.com LinkedIn:   / ahmed-mahmoud-datamindai   GitHub: https://github.com/AhmedMahmoud2 ▶ Previous Episode Build a Production-Grade RAG Pipeline | Knowledge Layer in AI Solution Architecture    • AI Solution Architecture Masterclass Ep4 –...   ▶ Next Episode AI Architecture Masterclass – Agentic Layer | Routing, Context & Multi-Agent Orchestration    • AI Architecture Masterclass Ep6 – Agentic ...