Build the engineering foundations required to design and develop production-grade AI systems—from Python and FastAPI to databases, security, semantic search, RAG, LLM architecture, and AI application performance.Go beyond Python programming and start thinking like an AI Engineer.The AI Engineer — Volume I takes you from professional Python engineering to the foundations of modern AI application development.You will build the engineering knowledge required to create reliable AI systems—not just experimental notebooks or simple API calls.A project-based AI engineering book covering Python production engineering, FastAPI, PostgreSQL, authentication, testing, reliability, embeddings, semantic search, RAG, LLM architecture, AI pipelines, caching, and performance optimization.AI EngineeringAI EngineerArtificial IntelligenceGenerative AILLMLarge Language ModelsPythonFastAPIRAGRetrieval Augmented GenerationSemantic SearchEmbeddingsVector SearchLLM ApplicationsAI SystemsMachine Learning EngineeringBackend EngineeringProduction AIAI ArchitectureSoftware Engineering
This book will take you on a journey from the 90s to the now. In our travels, we’ll encounter many frameworks and libraries. For instance, Knockout, React, Angular, Vue, Astro, Fresh, and many more. These meetings will increase our knowledge of their patterns, story, and use cases.
Develop a test suite for a Marionette app and find out how writing more code actually makes you more productive. You'll also witness how testing leads you to writing better, decoupled code.
Bring your applications to the next level, using these handy solutions to common application development challenges.
Be more productive with Backbone.js: Marionette handles the boilerplate code, letting you focus on your application's specifics. Develop a complete Marionette.js app with this book, and you'll be comfortable with the library (whether you're new to web apps, or looking to quickly master yet another framework).