Enterprise AI in the Cloud: A Practical Guide to Deploying End-to-End Machine Learning and ChatGPT Solutions...

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Rabi Jay

Enterprise AI in the Cloud

A Practical Guide to Deploying End-to-End Machine Learning and ChatGPT Solutions

Rabi Jay

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English

John Wiley & Sons Inc
02 January 2024

Computer science; Artificial intelligence

Series: Tech Today

Embrace emerging AI trends and integrate your operations with cutting-edge solutions

Enterprise AI in the Cloud: A Practical Guide to Deploying End-to-End Machine Learning and ChatGPT Solutions is an indispensable resource for professionals and companies who want to bring new AI technologies like generative AI, ChatGPT, and machine learning (ML) into their suite of cloud-based solutions. If you want to set up AI platforms in the cloud quickly and confidently and drive your business forward with the power of AI, this book is the ultimate go-to guide. The author shows you how to start an enterprise-wide AI transformation effort, taking you all the way through to implementation, with clearly defined processes, numerous examples, and hands-on exercises. You'll also discover best practices on optimizing cloud infrastructure for scalability and automation.

Enterprise AI in the Cloud helps you gain a solid understanding of:

AI-First Strategy: Adopt a comprehensive approach to implementing corporate AI systems in the cloud and at scale, using an AI-First strategy to drive innovation State-of-the-Art Use Cases: Learn from emerging AI/ML use cases, such as ChatGPT, VR/AR, blockchain, metaverse, hyper-automation, generative AI, transformer models, Keras, TensorFlow in the cloud, and quantum machine learning Platform Scalability and MLOps (ML Operations): Select the ideal cloud platform and adopt best practices on optimizing cloud infrastructure for scalability and automation AWS, Azure, Google ML: Understand the machine learning lifecycle, from framing problems to deploying models and beyond, leveraging the full power of Azure, AWS, and Google Cloud platforms AI-Driven Innovation Excellence: Get practical advice on identifying potential use cases, developing a winning AI strategy and portfolio, and driving an innovation culture Ethical and Trustworthy AI Mastery: Implement Responsible AI by avoiding common risks while maintaining transparency and ethics Scaling AI Enterprise-Wide: Scale your AI implementation using Strategic Change Management, AI Maturity Models, AI Center of Excellence, and AI Operating Model

Whether you're a beginner or an experienced AI or MLOps engineer, business or technology leader, or an AI student or enthusiast, this comprehensive resource empowers you to confidently build and use AI models in production, bridging the gap between proof-of-concept projects and real-world AI deployments.

With over 300 review questions, 50 hands-on exercises, templates, and hundreds of best practice tips to guide you through every step of the way, this book is a must-read for anyone seeking to accelerate AI transformation across their enterprise.

By: Rabi Jay
Imprint: John Wiley & Sons Inc
Country of Publication: United States
Dimensions: Height: 236mm, Width: 188mm, Spine: 31mm
Weight: 726g
ISBN: 9781394213054
ISBN 10: 1394213050
Series: Tech Today
Pages: 528
Publication Date: 02 January 2024
Audience: Professional and scholarly , Undergraduate
Format: Paperback
Publisher's Status: Active

Introduction xvii Part I: Introduction Chapter 1: Enterprise Transformation with AI in the Cloud 3 Chapter 2: Case Studies of Enterprise AI in the Cloud 19 Part II: Strategizing and Assessing for Ai Chapter 3: Addressing the Challenges with Enterprise AI 31 Chapter 4: Designing AI Systems Responsibly 41 Chapter 5: Envisioning and Aligning Your AI Strategy 50 Chapter 6: Developing An AI Strategy and Portfolio 57 Chapter 7: Managing Strategic Change 66 Part III: Planning and Launching a Pilot Project Chapter 8: Identifying Use Cases for Your AI/ml Project 79 Chapter 9: Evaluating AI/ml Platforms and Services 106 Chapter 10: Launching Your Pilot Project 152 Part IV: Building and Governing Your Team Chapter 11: Empowering Your People Through Org Change Management 163 Chapter 12: Building Your Team 173 Part V: Setting Up Infrastructure and Managing Operations Chapter 13: Setting Up An Enterprise AI Cloud Platform Infrastructure 187 Chapter 14: Operating Your AI Platform with Mlops Best Practices 217 Part VI: Processing Data and Modeling Chapter 15: Process Data and Engineer Features in The Cloud 243 Chapter 16: Choosing Your AI/ml Algorithms 268 Chapter 17: Training, Tuning, and Evaluating Models 315 Part VII: Deploying and Monitoring Models Chapter 18: Deploying Your Models Into Production 345 Chapter 19: Monitoring Models 361 Chapter 20: Governing Models for Bias and Ethics 377 Part VIII: Scaling and Transforming AI Chapter 21: Using the AI Maturity Framework to Transform Your Business 391 Chapter 22: Setting Up Your AI Coe 407 Chapter 23: Building Your AI Operating Model and Transformation Plan 416 Part IX: Evolving and Maturing AI Chapter 24: Implementing Generative AI Use Cases With Chatgpt for the Enterprise 433 Chapter 25: Planning for the Future of AI 465 Chapter 26: Continuing Your AI Journey 479 Index 485

RABI JAY is a recognized IT expert with over 15 years of experience working in roles such as VP of Architecture, Digital Platform Strategy Lead, and Global Alliance Manager at Deloitte Consulting, as well as at HCL America and SapientRazorfish. He has been instrumental in driving large-scale, enterprise-level Cloud and AI transformations across diverse industries like retail, telecom, finance, and tech. He holds sought-after certifications in AWS Machine Learning, AWS Solutions Architect, and Microsoft Azure. You can connect with Rabi through his authoritative LinkedIn newsletter, Enterprise AI Transformation.