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

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

"Embrace emerging AI trends and integrate your operations with cutting-edge solutions Enterprise AI in the 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 gen...

Full description

Bibliographic Details
Main Author: Jay, Rabi (-)
Format: eBook
Language:Inglés
Published: Newark : John Wiley & Sons, Incorporated 2024.
Edition:1st ed
Series:Tech Today Series
Subjects:
Artificial intelligence > Computer programs.
Technology.
See on Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009811321606719
Table of Contents:
  • Cover
  • Title Page
  • Copyright Page
  • Acknowledgments
  • About the Author
  • About the Technical Editor
  • Contents
  • Introduction
  • How This Book Is Organized
  • Who Should Read This Book?
  • Data Scientists and AI Teams
  • IT Leaders and Teams
  • Students and Academia
  • Consultants and Advisors
  • Business Strategists and Leaders
  • C-Level Executives
  • Why You Should Read This Book
  • Unique Features
  • Comprehensive Coverage of All Aspects of Enterprise-wide AI Transformation
  • Case Study Approach
  • Coverage of All Major Cloud Platforms
  • Discussion of Nontechnical Aspects of AI
  • Best Practices for MLOps and AI Governance
  • Up-to-Date Content
  • Hands-on Approach
  • Part I Introduction
  • Chapter 1 Enterprise Transformation with AI in the Cloud
  • Understanding Enterprise AI Transformation
  • Why Some Companies Succeed at Implementing AI and ML While Others Fail
  • Transform Your Company by Integrating AI, ML and Gen AI into Your Business Processes
  • Adopt AI-First to Become World-Class
  • Importance of an AI-First Strategy
  • Prioritize AI and Data Initiatives
  • Leveraging Enterprise AI Opportunities
  • Enable One-to-One, Personalized, Real-Time Service for Customers at Scale
  • Enterprise-wide AI Opportunities
  • Growing Industry Adoption of AI
  • Workbook Template - Enterprise AI Transformation Checklist
  • Summary
  • Review Questions
  • Answer Key
  • Chapter 2 Case Studies of Enterprise AI in the Cloud
  • Case Study 1: The U.S. Government and the Power of Humans and Machines Working Together to Solve Problems at Scale
  • Revolutionizing Operations Management with AI/ML
  • Enabling Solutions for Improved Operations
  • Case Study 2: Capital One and How It Became a Leading Technology Organization in a Highly Regulated Environment
  • Building Amazing Experiences Due to Data Consolidation.
  • Becoming Agile and Scalable by Moving Data Centers Into the Cloud
  • Building a Resilient System by Embracing Cloud-Native Principles
  • Impact of Cloud-First Thinking on DevOps, Agile Development, and Machine Learning
  • Becoming an AI-First Company: From Cloud Adoption to Thrilling Customer Experiences
  • Case Study 3: Netflix and the Path Companies Take to Become World-Class
  • Cloud and AI Technology: A Game-Changer for Netflix's Business Model and Success
  • Cloud Infrastructure and AI Adoption Drives Process Transformation
  • Process Transformation Drives Organizational Change
  • Workbook Template - AI Case Study
  • Summary
  • Review Questions
  • Answer Key
  • Part II Strategizing and Assessing for AI
  • Chapter 3 Addressing the Challenges with Enterprise AI
  • Challenges Faced by Companies Implementing Enterprise-wide AI
  • Business-Related Challenges
  • Data- and Model-Related Challenges
  • Platform-Related Challenges
  • How Digital Natives Tackle AI Adoption
  • They Are Willing to Take Risks
  • They Have an Advantage in Data Collection and Curation Capabilities
  • They Attract Top Talent Through Competitive Compensation and Perks
  • Get Ready: AI Transformation Is More Challenging Than Digital Transformation
  • Complexities of Skill Sets, Technology, and Infrastructure Integration
  • The Importance of Data Infrastructure and Governance
  • Change Management to Redefine Work Processes and Employee Mindsets
  • Regulatory Concerns: Addressing Bias, Ethical, Privacy, and Accountability Risks
  • Choosing Between Smaller PoC Point Solutions and Large-Scale AI Initiatives
  • The Challenges of Implementing a Large-Scale AI Initiative
  • Navigate the Moving Parts, Stakeholders, and Technical Infrastructure
  • Resource Allocation Challenges in Large-Scale AI Initiatives
  • Overcome Resistance to Change.
  • Data Security, Privacy, Ethics, Compliance, and Reputation
  • Build a Business Case for Large-Scale AI Initiatives
  • Factors to Consider
  • Workbook Template: AI Challenges Assessment
  • Summary
  • Review Questions
  • Answer Key
  • Chapter 4 Designing AI Systems Responsibly
  • The Pillars of Responsible AI
  • Robust AI
  • Collaborative AI
  • Trustworthy AI
  • Scalable AI
  • Human-centric AI
  • Workbook Template: Responsible AI Design Template
  • Summary
  • Review Questions
  • Answer Key
  • Chapter 5 Envisioning and Aligning Your AI Strategy
  • Step-by-Step Methodology for Enterprise-wide AI
  • The Envision Phase
  • The Align Phase
  • Workbook Template: Vision Alignment Worksheet
  • Summary
  • Review Questions
  • Answer Key
  • Chapter 6 Developing an AI Strategy and Portfolio
  • Leveraging Your Organizational Capabilities for Competitive Advantage
  • Focus Areas to Build Your Competitive Advantage
  • Driving Competitive Advantage Through AI
  • Initiating Your Strategy and Plan to Kickstart Enterprise AI
  • Manage Your AI Strategy, Portfolio, Innovation, Product Lifecycle, and Partnerships
  • Define Your AI Strategy to Achieve Business Outcomes
  • Prioritize Your Portfolio
  • Strategy and Execution Across Phases
  • Workbook Template: Business Case and AI Strategy
  • Summary
  • Review Questions
  • Answer Key
  • Chapter 7 Managing Strategic Change
  • Accelerating Your AI Adoption with Strategic Change Management
  • Phase 1: Develop an AI Acceleration Charter and Governance Mechanisms for Your AI Initiative
  • Phase 2: Ensure Leadership Alignment
  • Phase 3: Create a Change Acceleration Strategy
  • Workbook Template: Strategic Change Management Plan
  • Summary
  • Review Questions
  • Answer Key
  • Part III Planning and Launching a Pilot Project
  • Chapter 8 Identifying Use Cases for Your AI/ML Project
  • The Use Case Identification Process Flow.
  • Educate Everyone as to How AI/ML Can Solve Business Problems
  • Define Your Business Objectives
  • Identify the Pain Points
  • Start with Root-Cause Analysis
  • Identify the Success Metrics
  • Explore the Latest Industry Trends
  • Review AI Applications in Various Industries
  • Map the Use Case to the Business Problem
  • Prioritizing Your Use Cases
  • Define the Impact Criteria
  • Define the Feasibility Criteria
  • Assess the Impact
  • Assess the Feasibility
  • Prioritize the Use Cases
  • Review and Refine the Criteria
  • Choose the Right Model
  • Use Cases to Choose From
  • AI Use Cases for DevOps
  • AI for Healthcare and Life Sciences
  • AI Enabled Contact Center Use Cases
  • Business Metrics Analysis
  • Content Moderation
  • AI for Financial Services
  • Cybersecurity
  • Digital Twinning
  • Identity Verification
  • Intelligent Document Processing
  • Intelligent Search
  • Machine Translation
  • Media Intelligence
  • ML Modernization
  • ML-Powered Personalization
  • Computer Vision
  • Personal Protective Equipment
  • Generative AI
  • Workbook Template: Use Case Identification Sheet
  • Summary
  • Review Questions
  • Answer Key
  • Chapter 9 Evaluating AI/ML Platforms and Services
  • Benefits and Factors to Consider When Choosing an AI/ML Service
  • Benefits of Using Cloud AI/ML Services
  • Factors to Consider When Choosing an AI/ML Service
  • AWS AI and ML Services
  • AI Services
  • Amazon SageMaker
  • AI Frameworks
  • Differences Between Machine Learning Algorithms, Models, and Services
  • Core AI Services
  • Text and Document Services
  • Chatbots: Amazon Lex
  • Speech
  • Vision Services
  • Specialized AI Services
  • Business Processing Services
  • Kendra for Search
  • Code and DevOps
  • Industrial Solutions
  • Healthcare Solutions
  • Machine Learning Services
  • Amazon SageMaker
  • Amazon SageMaker Canvas
  • SageMaker Studio Lab.
  • The Google AI/ML Services Stack
  • For Data Scientists
  • For Developers
  • The Microsoft AI/ ML Services Stack
  • Azure Applied AI Services
  • Azure Cognitive Services
  • Azure Machine Learning
  • Other Enterprise Cloud AI Platforms
  • Dataiku
  • DataRobot
  • KNIME
  • IBM Watson
  • Salesforce Einstein AI
  • Oracle Cloud AI
  • Workbook Template: AI/ML Platform Evaluation Sheet
  • Summary
  • Review Questions
  • Answer Key
  • Chapter 10 Launching Your Pilot Project
  • Launching Your Pilot
  • Planning for Launch
  • Recap of the Envision Phase
  • Planning for the Machine Learning Project
  • Following the Machine Learning Lifecycle
  • Business Goal Identification
  • Machine Learning Problem Framing
  • Data Processing
  • Model Development
  • Model Deployment
  • Model Monitoring
  • Workbook Template: AI/ML Pilot Launch Checklist
  • Summary
  • Review Questions
  • Answer Key
  • Part IV Building and Governing Your Team
  • Chapter 11 Empowering Your People Through Org Change Management
  • Succeeding Through a People-centric Approach
  • Evolve Your Culture for AI Adoption, Innovation, and Change
  • Redesign Your Organization for Agility and Innovation with AI
  • Aligning Your Organization Around AI Adoption to Achieve Business Outcomes
  • Workbook Template: Org Change Management Plan
  • Summary
  • Review Questions
  • Answer Key
  • Note
  • Chapter 12 Building Your Team
  • Understanding the Roles and Responsibilities in an ML Project
  • Build a Cross-Functional Team for AI Transformation
  • Adopt Cloud and AI to Transform Current Roles
  • Customize Roles to Suit Your Business Goals and Needs
  • Workbook Template: Team Building Matrix
  • Summary
  • Review Questions
  • Answer Key
  • Part V Setting Up Infrastructure and Managing Operations
  • Chapter 13 Setting Up an Enterprise AI Cloud Platform Infrastructure
  • Reference Architecture Patterns for Typical Use Cases.
  • Customer 360-Degree Architecture.

Similar Items