About this item
Highlights
- Understand and apply the design patterns outlined in this book to design, develop, and deploy scalable AI solutions that meet your organization's needs and drive innovation in the era of intelligent automation.
- About the Author: Abhishek Mishra is a seasoned data science and analytics professional with extensive expertise in information technology services and products.
- 256 Pages
- Computers + Internet, Intelligence (AI) & Semantics
Description
Book Synopsis
Understand and apply the design patterns outlined in this book to design, develop, and deploy scalable AI solutions that meet your organization's needs and drive innovation in the era of intelligent automation.
This book begins with an overview of scalable AI systems and the importance of design patterns in creating robust intelligent solutions. It covers fundamental concepts and techniques for achieving scalability in AI systems, including data engineering practices and strategies. The book also addresses scalable algorithms, models, infrastructure, and architecture considerations. Additionally, it discusses deployment, productionization, real-time and streaming data, edge computing, governance, and ethics in scalable AI. Real-world case studies and best practices are presented, along with insights into future trends and emerging technologies.
The book focuses on scalable AI and design patterns, providing an understanding of the challenges involved in developing AI systems that can handle large amounts of data, complex algorithms, and real-time processing. By exploring scalability, you will be empowered to design and implement AI solutions that can adapt to changing data requirements.
What You Will Learn
- Develop scalable AI systems that can handle large volumes of data, complex algorithms, and real-time processing
- Know the significance of design patterns in creating robust intelligent solutions
- Understand scalable algorithms and models to handle extensive data and computing requirements and build scalable AI systems
- Be aware of the ethical implications of scalable AI systems
Who This Book Is For
AI practitioners, data scientists, and software engineers with intermediate-level AI knowledge and experience
From the Back Cover
Understand and apply the design patterns outlined in this book to design, develop, and deploy scalable AI solutions that meet your organization's needs and drive innovation in the era of intelligent automation.
This book begins with an overview of scalable AI systems and the importance of design patterns in creating robust intelligent solutions. It covers fundamental concepts and techniques for achieving scalability in AI systems, including data engineering practices and strategies. The book also addresses scalable algorithms, models, infrastructure, and architecture considerations. Additionally, it discusses deployment, productionization, real-time and streaming data, edge computing, governance, and ethics in scalable AI. Real-world case studies and best practices are presented, along with insights into future trends and emerging technologies.
The book focuses on scalable AI and design patterns, providing an understanding of the challenges involved in developing AI systems that can handle large amounts of data, complex algorithms, and real-time processing. By exploring scalability, you will be empowered to design and implement AI solutions that can adapt to changing data requirements.
What You Will Learn
- Develop scalable AI systems that can handle large volumes of data, complex algorithms, and real-time processing
- Know the significance of design patterns in creating robust intelligent solutions
- Understand scalable algorithms and models to handle extensive data and computing requirements and build scalable AI systems
- Be aware of the ethical implications of scalable AI systems
Review Quotes
"Scalable AI and design patterns is a valuable resource for software architects, developers, and data scientists who are working on creating scalable artificial intelligence (AI) systems. ... The book offers practical examples and real-world case studies to help readers apply these patterns to their own AI projects. While the book is geared toward practitioners with a solid foundation in AI and cloud technologies, it provides an excellent roadmap for anyone looking to build robust, scalable AI systems." (Wael Badawy, Computing Reviews, November 22, 2024)
About the Author
Abhishek Mishra is a seasoned data science and analytics professional with extensive expertise in information technology services and products. With a remarkable 15-year track record, Abhishek has leveraged his data science knowledge and engineering skills to analyze vast datasets, interpret findings, and communicate actionable insights to drive effective business decision making. He has successfully led global analytics teams, developed cutting-edge machine learning solutions, and formulated data analytics strategies for esteemed organizations such as Marsh and McLennan, Fiserv India Pvt Ltd, and Deloitte Inc.