
Sách gia công
Thể loại:Computers - Artificial Intelligence (AI)
Năm:2023
In lần thứ:1
Nhà xuát bản:Apress
Ngôn ngữ:english
Trang:390
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
Who this book is for:
Data scientists and AI consultants with programming skills in Python and driven to succeed in AI.
About the Author
Barry
Walsh is a software-delivery consultant and AI trainer at Pairview with
a background in exploiting complex business data to optimize and
de-risk energy assets at ABB/Ventyx, Infosys, E.ON, Centrica, and his
own start-up ce.tech. He has a proven track record of providing
consultancy services in Data Science, BI, and Business Analysis to
businesses in Energy, IT, FinTech, Telco, Retail,