Productionizing AI
Apress (Verlag)
978-1-4842-8816-0 (ISBN)
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.
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, and Healthcare, Barry has been at the apex of analytics and AI solutions delivery for 20 years. Besides being passionate about Enterprise AI, Barry spends his spare time with his wife and 8-year-old son, playing the piano, riding long bike rides (and a marathon on a broken toe this year), eating out whenever possible or getting his daily coffee fix.
Chapter 1: Introduction to AI & the AI Ecosystem.- Chapter 2: AI Best Practise & DataOps.- Chapter 3: Data Ingestion for AI.- Chapter 4: Machine Learning on Cloud.- Chapter 5: Neural Networks and Deep Learning.- Chapter 6: The Employer’s Dream: AutoML, AutoAI and the rise of NoLo UIs.- Chapter 7: AI Full Stack: Application Development.- Chapter 8: AI Case Studies.- Chapter 9: Deploying an AI Solution (Productionizing & Containerization).- Chapter 10: Natural Language Processing.- Postscript.
Erscheinungsdatum | 10.01.2023 |
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Zusatzinfo | 158 Illustrations, color; 16 Illustrations, black and white; XXV, 373 p. 174 illus., 158 illus. in color. |
Verlagsort | Berkley |
Sprache | englisch |
Maße | 178 x 254 mm |
Themenwelt | Mathematik / Informatik ► Informatik ► Programmiersprachen / -werkzeuge |
Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
Schlagworte | Artitificial Intelligence • AutoML • Containerisation • data orchestration • data pipelines • Deep learning • machine learning • Natural Language Processing • Productionizing • Python |
ISBN-10 | 1-4842-8816-5 / 1484288165 |
ISBN-13 | 978-1-4842-8816-0 / 9781484288160 |
Zustand | Neuware |
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