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Ready to build applications using generative AI? This practical book outlines the process necessary to design and build production grade AI services with a FastAPI web server that communicate seamlessly with databases, payment systems, and external APIs. You'll learn how to develop autonomous generative AI agents that stream outputs in real-time and interact with other models. Web developers, data scientists, and DevOps engineers will learn to implement end-to-end production-ready services that leverage generative AI.
You'll learn design patterns to manage software complexity, implement FastAPI lifespan for AI model integration, handle long-running generative tasks, perform content filtering, cache outputs, implement retrieval augmented generation (RAG) with a vector database, implement usage/cost monitoring and tracking, protect services with your own authentication and authorization mechanisms, and effectively control stream outputs directly from GenAI models. You'll explore efficient testing methods for AI outputs, validation against databases, and deployment patterns using Docker for robust microservices in the cloud.
- • Build generative services that interact with databases, external APIs, and more • Learn how to load AI models into a FastAPI lifecycle memory • Monitor and log model requests and responses within services • Use authentication and authorization patterns hooked with generative models • Handle and cache long-running inference tasks • Stream model outputs via streaming events and WebSockets into browsers or files • Automate the retraining process of generative models by exposing event-driven endpoints
Ali Parandeh is a Chartered Engineer with the UK Engineering Council and a Microsoft and Google certified developer, data engineer, and data scientist.
Ready to build applications using generative AI? This practical book outlines the process necessary to design and build production grade AI services with a FastAPI web server that communicate seamlessly with databases, payment systems, and external APIs. You'll learn how to develop autonomous generative AI agents that stream outputs in real-time and interact with other models. Web developers, data scientists, and DevOps engineers will learn to implement end-to-end production-ready services that leverage generative AI.
You'll learn design patterns to manage software complexity, implement FastAPI lifespan for AI model integration, handle long-running generative tasks, perform content filtering, cache outputs, implement retrieval augmented generation (RAG) with a vector database, implement usage/cost monitoring and tracking, protect services with your own authentication and authorization mechanisms, and effectively control stream outputs directly from GenAI models. You'll explore efficient testing methods for AI outputs, validation against databases, and deployment patterns using Docker for robust microservices in the cloud.
- • Build generative services that interact with databases, external APIs, and more • Learn how to load AI models into a FastAPI lifecycle memory • Monitor and log model requests and responses within services • Use authentication and authorization patterns hooked with generative models • Handle and cache long-running inference tasks • Stream model outputs via streaming events and WebSockets into browsers or files • Automate the retraining process of generative models by exposing event-driven endpoints
Ali Parandeh is a Chartered Engineer with the UK Engineering Council and a Microsoft and Google certified developer, data engineer, and data scientist.
As a passionate educator, Ali dedicates his free time to teaching data science and web development through meetups and online platforms. In 2019, he founded London's Beginners Machine Learning (BML) group, a Microsoft-sponsored meetup aimed at helping professionals break into the field of Data Science & AI and obtain cloud certifications which has since grown to over 1,500 members.
| Erscheinungsjahr: | 2025 |
|---|---|
| Fachbereich: | Datenkommunikation, Netze & Mailboxen |
| Genre: | Importe, Informatik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Taschenbuch |
| Inhalt: | Einband - flex.(Paperback) |
| ISBN-13: | 9781098160302 |
| ISBN-10: | 1098160304 |
| Sprache: | Englisch |
| Einband: | Kartoniert / Broschiert |
| Autor: | Parandeh, Ali |
| Hersteller: | O'Reilly Media |
| Verantwortliche Person für die EU: | Libri GmbH, Europaallee 1, D-36244 Bad Hersfeld, gpsr@libri.de |
| Maße: | 233 x 177 x 33 mm |
| Von/Mit: | Ali Parandeh |
| Erscheinungsdatum: | 30.04.2025 |
| Gewicht: | 0,822 kg |
As a passionate educator, Ali dedicates his free time to teaching data science and web development through meetups and online platforms. In 2019, he founded London's Beginners Machine Learning (BML) group, a Microsoft-sponsored meetup aimed at helping professionals break into the field of Data Science & AI and obtain cloud certifications which has since grown to over 1,500 members.
| Erscheinungsjahr: | 2025 |
|---|---|
| Fachbereich: | Datenkommunikation, Netze & Mailboxen |
| Genre: | Importe, Informatik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Taschenbuch |
| Inhalt: | Einband - flex.(Paperback) |
| ISBN-13: | 9781098160302 |
| ISBN-10: | 1098160304 |
| Sprache: | Englisch |
| Einband: | Kartoniert / Broschiert |
| Autor: | Parandeh, Ali |
| Hersteller: | O'Reilly Media |
| Verantwortliche Person für die EU: | Libri GmbH, Europaallee 1, D-36244 Bad Hersfeld, gpsr@libri.de |
| Maße: | 233 x 177 x 33 mm |
| Von/Mit: | Ali Parandeh |
| Erscheinungsdatum: | 30.04.2025 |
| Gewicht: | 0,822 kg |
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