Читать книгу Enterprise AI For Dummies - Zachary Jarvinen - Страница 3

1  Cover

2  Introduction About This Book Strong, Weak, General, and Narrow Foolish Assumptions Icons Used in This Book Beyond the Book Where to Go from Here

3  Part 1: Exploring Practical AI and How It Works Chapter 1: Demystifying Artificial Intelligence Understanding the Demand for AI Identifying the Enabling Technology Discovering How It Works Chapter 2: Looking at Uses for Practical AI Recognizing AI When You See It Benefits of AI for Your Enterprise Chapter 3: Preparing for Practical AI Democratizing AI Visualizing Results Digesting Data Defining Use Cases Choosing a Model Chapter 4: Implementing Practical AI The AI Competency Hierarchy Scoping, Setting Up, and Running an Enterprise AI Project Creating a High-Performing Data Science Team The Critical Role of Internal and External Partnerships Weighing Your Options: Build versus Buy Hosting in the Cloud versus On Premises

4  Part 2: Exploring Vertical Market Applications Chapter 5: Healthcare/HMOs: Streamlining Operations Surfing the Data Tsunami Breaking the Iron Triangle with Data Matching Algorithms to Benefits Examining the Use Cases Chapter 6: Biotech/Pharma: Taming the Complexity Navigating the Compliance Minefield Weaponizing the Medical, Legal, and Regulatory Review Enlisting Algorithms for the Cause Examining the Use Cases Chapter 7: Manufacturing: Maximizing Visibility Peering through the Data Fog Clearing the Fog Clarifying the Connection to the Code Examining the Use Cases Chapter 8: Oil and Gas: Finding Opportunity in Chaos Wrestling with Volatility Pouring Data on Troubled Waters Wrangling Algorithms for Fun and Profit Examining the Use Cases Chapter 9: Government and Nonprofits: Doing Well by Doing Good Battling the Budget Optimizing Past the Obstacles Connecting the Tools to the Job Examining the Use Cases Chapter 10: Utilities: Renewing the Business Coping with the Consumer Mindset Utilizing Big Data Connecting Algorithms to Goals Examining the Use Cases Chapter 11: Banking and Financial Services: Making It Personal Finding the Bottom Line in the Data Leveraging Big Data Restructuring with Algorithms Examining the Use Cases Chapter 12: Retail: Reading the Customer’s Mind Looking for a Crystal Ball Reading the Customer’s Mail Looking Behind the Curtain Examining the Use Cases Chapter 13: Transportation and Travel: Tuning Up Your Ride Avoiding the Bumps in the Road Planning the Route Checking Your Tools Examining the Use Cases Chapter 14: Telecommunications: Connecting with Your Customers Listening Past the Static Finding the Signal in the Noise Looking Inside the Box Examining the Use Cases Chapter 15: Legal Services: Cutting Through the Red Tape Climbing the Paper Mountain Planting Your Flag at the Summit Linking Algorithms with Results Examining the Use Cases Chapter 16: Professional Services: Increasing Value to the Customer Exploring the AI Pyramid Climbing the AI Pyramid Unearthing the Algorithmic Treasures Examining the Use Cases Chapter 17: Media and Entertainment: Beating the Gold Rush Mining for Content Striking It Rich Assaying the Algorithms Examining the Use Cases

5  Part 3: Exploring Horizontal Market Applications Chapter 18: Voice of the Customer/Citizen: Finding Coherence in the Cacophony Hearing the Message in the Media Delivering What They Really Want Answering the Right Questions Examining Key Industries Chapter 19: Asset Performance Optimization: Increasing Value by Extending Lifespans Spying on Your Machines Fixing It Before It Breaks Learning from the Future Examining the Use Cases Chapter 20: Intelligent Recommendations: Getting Personal Making Friends by the Millions Reading Minds Knowing Which Buttons to Push Examining Key Industries Chapter 21: Content Management: Finding What You Want, When You Want It Introducing the Square Peg to the Round Hole Finding Content at the Speed of AI Expanding Your Toolbox Examining the Use Cases Chapter 22: AI-Enhanced Content Capture: Gathering All Your Eggs into the Same Basket Counting All the Chickens, Hatched and Otherwise Monetizing All the Piggies, Little and Otherwise Getting All Your Ducks in a Row Examining Key Industries Chapter 23: Regulatory Compliance and Legal Risk Reduction: Hitting the Bullseye on a Moving Target Dodging Bullets Shooting Back Building an Arsenal Examining the Use Cases Chapter 24: Knowledge Assistants and Chatbots: Monetizing the Needle in the Haystack Missing the Trees for the Forest Hearing the Tree Fall Making Trees from Acorns Examining the Use Cases Chapter 25: AI-Enhanced Security: Staying Ahead by Watching Your Back Closing the Barn Door Locking the Barn Door Knowing Which Key to Use Examining the Use Cases

6  Part 4: The Part of Tens Chapter 26: Ten Ways AI Will Influence the Next Decade Proliferation of AI in the Enterprise AI Will Reach Across Functions AI R&D Will Span the Globe The Data Privacy Iceberg Will Emerge More Transparency in AI Applications Augmented Analytics Will Make It Easier Rise of Intelligent Text Mining Chatbots for Everyone Ethics Will Emerge for the AI Generation Rise of Smart Cities through AI Chapter 27: Ten Reasons Why AI Is Not a Panacea AI Is Not Human Pattern Recognition Is Not the Same As Understanding AI Cannot Anticipate Black Swan Events AI Might Be Democratized, but Data Is Not AI Is Susceptible to Inherent Bias in the Data AI Is Susceptible to Poor Problem Framing AI Is Blind to Data Ambiguity AI Will Not, or Cannot, Explain Its Own Results AI Is Not Immune to the Law of Unintended Consequences

7  Index

8  About the Author

9  Advertisement Page

10  Connect with Dummies

11  End User License Agreement