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Enterprise AI in the Cloud
A Practical Guide to Deploying End-to-End Machine Learning and ChatGPT Solutions
Rabi Jay (Author)
9781394213054, Wiley
Paperback / softback, published 2 January 2024
528 pages
23.6 x 18.8 x 3.1 cm, 0.726 kg
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: 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.
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
Subject Areas: Computer science [UY]
