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Book Description

Enterprise Artificial Intelligence Transformation

AI is everywhere. From doctor's offices to cars and even refrigerators, AI technology is quickly infiltrating our daily lives. AI has the ability to transform simple tasks into technological feats at a human level. This will change the world, plain and simple. That's why AI mastery is such a sought-after skill for tech professionals.

Author Rashed Haq is a subject matter expert on AI, having developed AI and data science strategies, platforms, and applications for Publicis Sapient's clients for over 10 years. He shares that expertise in the new book, Enterprise Artificial Intelligence Transformation.

The first of its kind, this book grants technology leaders the insight to create and scale their AI capabilities and bring their companies into the new generation of technology. As AI continues to grow into a necessary feature for many businesses, more and more leaders are interested in harnessing the technology within their own organizations. In this new book, leaders will learn to master AI fundamentals, grow their career opportunities, and gain confidence in machine learning.

Enterprise Artificial Intelligence Transformation covers a wide range of topics, including:

  • Real-world AI use cases and examples
  • Machine learning, deep learning, and slimantic modeling
  • Risk management of AI models
  • AI strategies for development and expansion
  • AI Center of Excellence creating and management

If you're an industry, business, or technology professional that wants to attain the skills needed to grow your machine learning capabilities and effectively scale the work you're already doing, you'll find what you need in Enterprise Artificial Intelligence Transformation.

Table of Contents

  1. Cover
  2. Foreword: Artificial Intelligence and the New Generation of Technology Building Blocks
  3. Prologue: A Guide to This Book
  4. Part I: A Brief Introduction to Artificial Intelligence
    1. Chapter 1: A Revolution in the Making
      1. The Impact of the Four Revolutions
      2. AI Myths and Reality
      3. The Data and Algorithms Virtuous Cycle
      4. The Ongoing Revolution – Why Now?
      5. AI: Your Competitive Advantage
      6. Notes
    2. Chapter 2: What Is AI and How Does It Work?
      1. The Development of Narrow AI
      2. The First Neural Network
      3. Machine Learning
      4. Supervised, Unsupervised, and Semisupervised Learning
      5. Making Data More Useful
      6. Semantic Reasoning
      7. Applications of AI
      8. Notes
  5. Part II: Artificial Intelligence in the Enterprise
    1. Chapter 3: AI in E-Commerce and Retail
      1. Digital Advertising
      2. Marketing and Customer Acquisition
      3. Cross-Selling, Up-Selling, and Loyalty
      4. Business-to-Business Customer Intelligence
      5. Dynamic Pricing and Supply Chain Optimization
      6. Digital Assistants and Customer Engagement
      7. Notes
    2. Chapter 4: AI in Financial Services
      1. Anti-Money Laundering
      2. Loans and Credit Risk
      3. Predictive Services and Advice
      4. Algorithmic and Autonomous Trading
      5. Investment Research and Market Insights
      6. Automated Business Operations
      7. Notes
    3. Chapter 5: AI in Manufacturing and Energy
      1. Optimized Plant Operations and Assets Maintenance
      2. Automated Production Lifecycles
      3. Supply Chain Optimization
      4. Inventory Management and Distribution Logistics
      5. Electric Power Forecasting and Demand Response
      6. Oil Production
      7. Energy Trading
      8. Notes
    4. Chapter 6: AI in Healthcare
      1. Pharmaceutical Drug Discovery
      2. Clinical Trials
      3. Disease Diagnosis
      4. Preparation for Palliative Care
      5. Hospital Care
      6. Notes
  6. Part III: Building Your Enterprise AI Capability
    1. Chapter 7: Developing an AI Strategy
      1. Goals of Connected Intelligence Systems
      2. The Challenges of Implementing AI
      3. AI Strategy Components
      4. Steps to Develop an AI Strategy
      5. Some Assembly Required
      6. Moving Ahead
      7. Notes
    2. Chapter 8: The AI Lifecycle
      1. Defining Use Cases
      2. Collecting, Assessing, and Remediating Data
      3. Feature Engineering
      4. Selecting and Training a Model
      5. Managing Models
      6. Testing, Deploying, and Activating Models
      7. Conclusion
    3. Chapter 9: Building the Perfect AI Engine
      1. AI Platforms versus AI Applications
      2. What AI Platform Architectures Should Do
      3. Some Important Considerations
      4. AI Platform Architecture
      5. Notes
    4. Chapter 10: Managing Model Risk
      1. When Algorithms Go Wrong
      2. Mitigating Model Risk
      3. Model Risk Office
      4. Notes
    5. Chapter 11: Activating Organizational Capability
      1. Aligning Stakeholders
      2. Organizing for Scale
      3. AI Center of Excellence
      4. Structuring Teams for Project Execution
      5. Managing Talent and Hiring
      6. Data Literacy, Experimentation, and Data-Driven Decisions
      7. Conclusion
      8. Notes
  7. Part IV: Delving Deeper into AI Architecture and Modeling
    1. Chapter 12: Architecture and Technical Patterns
      1. AI Platform Architecture
      2. Technical Patterns
      3. Conclusion
    2. Chapter 13: The AI Modeling Process
      1. Defining the Use Case and the AI Task
      2. Selecting the Data Needed
      3. Setting Up the Notebook Environment and Importing Data
      4. Cleaning and Preparing the Data
      5. Understanding the Data Using Exploratory Data Analysis
      6. Feature Engineering
      7. Creating and Selecting the Optimal Model
      8. Note
  8. Part V: Looking Ahead
    1. Chapter 14: The Future of Society, Work, and AI
      1. AI and the Future of Society
      2. AI and the Future of Work
      3. Regulating Data and Artificial Intelligence
      4. The Future of AI: Improving AI Technology
      5. And This Is Just the Beginning
      6. Notes
  9. Further Reading
    1. General
    2. Society
    3. Work
  10. Acknowledgments
  11. About the Author
  12. Index
  13. End User License Agreement
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