Walsh B. - Productionizing AI [2023, PDF/EPUB, ENG] torrent

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Productionizing AI

Год издания: 2023
Автор: Walsh B.

Издательство: Apress
ISBN: 978-1-4842-8817-7
Язык: Английский

Формат: PDF/ePub
Качество: Издательский макет или текст (eBook)
Интерактивное оглавление: Да
Количество страниц: 390

Описание: This book is a guide to productionizing AI solutions using best-of-breed cloud services with workarounds to lower costs. Supplemented with step-by-step instructions covering data import through wrangling to partitioning and modeling through to inference and deployment, and augmented with plenty of Python code samples, the book has been written to accelerate the process of moving from script or notebook to app.
From an initial look at the context and ecosystem of AI solutions today, the book drills down from high-level business needs into best practices, working with stakeholders, and agile team collaboration. From there you’ll explore data pipeline orchestration, machine and deep learning, including working with and finding shortcuts using artificial neural networks such as AutoML and AutoAI. You’ll also learn about the increasing use of NoLo UIs through AI application development, industry case studies, and finally a practical guide to deploying containerized AI solutions.
The book is intended for those whose role demands overcoming budgetary barriers or constraints in accessing cloud credits to undertake the often difficult process of developing and deploying an AI solution.
What You Will Learn
- Develop and deliver production-grade AI in one month
- Deploy AI solutions at a low cost
- Work around Big Tech dominance and develop MVPs on the cheap
- Create demo-ready solutions without overly complex python scripts/notebooks
[spoiler="Примеры страниц"]

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[spoiler="Оглавление"]
About the Author xvii
About the Technical Reviewer xix
Preface xxi
Prologue xxiii
Chapter 1: Introduction to AI and the AI Ecosystem 1
Chapter 2: AI Best Practice and DataOps 41
Chapter 3: Data Ingestion for AI 75
Chapter 4: Machine Learning on Cloud 109
Chapter 5: Neural Networks and Deep Learning 133
Chapter 6: AutoML, AutoAI, and the Rise of NoLo UIs 187
Chapter 7: AI Full Stack: Application Development 211
Chapter 8: AI Case Studies 247
Chapter 9: Deploying an AI Solution (Productionizing and Containerization) 289
Chapter 10: Natural Language Processing 319
Postscript 359
Index 363
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