CONTEXT ENGINEERING (A.I.) Book 01: Fundamentals & Frameworks: Master Concepts to Optimize Interactions and Design High-Performance AI Models (AI & Machine Learning ENG) - Softcover

Buch 1 von 11: AI & Machine Learning ENG

Rodrigues, Diego

 
9798270074661: CONTEXT ENGINEERING (A.I.) Book 01: Fundamentals & Frameworks: Master Concepts to Optimize Interactions and Design High-Performance AI Models (AI & Machine Learning ENG)

Inhaltsangabe

CONTEXT ENGINEERING (A.I.) Book 01: Fundamentals & Frameworks Master Concepts to Optimize Interactions and Design High-Performance AI Models

This book is intended for students and professionals seeking to understand the concepts of Context Engineering to design, implement, and optimize Artificial Intelligence systems based on context-awareness and situational inference — the core of modern cognitive architectures.

Structured for practical application and integration with real frameworks, the content presents solid foundations and functional examples that connect semantic modeling, contextual memory, adaptive inference, and operational governance within AI ecosystems. It explores architectures, pipelines, and frameworks that support the new generation of contextual agents, focusing on efficiency, traceability, and scalability.

You will perform:

• Implementation of context pipelines using Python, LangChain, FAISS, Pinecone, and Milvus

• Structuring of contextual layers and cognitive orchestration with Semantic Kernel, CrewAI, and LangGraph

• Application of RAG (Retrieval-Augmented Generation) in contextual generation flows and expanded memory

• Configuration of vector databases, embeddings, and semantic search mechanisms with OpenAI and Hugging Face

• Context integration in adaptive UX, conversational interfaces, and cognitive automation via REST and WebSocket APIs

• Contextual governance and compliance with auditing, telemetry, and semantic versioning policies

• Monitoring and contextual performance metrics (precision, recall, coherence score, context drift detection)

• Scalability, caching, and load-balancing strategies in distributed architectures (Kubernetes, Redis, Kafka, Docker)

• Enterprise applications of Context Engineering in AWS, Azure, and Google Cloud environments

By the end, readers will gain conceptual and operational mastery to structure cognitive solutions capable of perceiving, interpreting, and acting based on contextual variables — unifying perception, reasoning, and action in highly responsive intelligent systems.

context engineering, context-aware systems, langchain, semantic kernel, crewai, langgraph, faiss, pinecone, milvus, vector database, embeddings, rag, llm, openai, hugging face, ai pipelines, python, kubernetes, redis, kafka, docker, aws, azure, gcp, adaptive ux, contextual governance, telemetry, compliance, situational inference, cognitive automation, contextual ai, applied artificial intelligence

Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.