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by Ben Mackenzie, Chad Meley, Atif Kureishy
Achieving Real Business Outcomes from Artificial Intelligence
Foreword
Acknowledgments
Our Customers
Our Talented Data Scientists
Industry Analysts
Our Community
1. Artificial Intelligence and Our World
A New Age of Computation
The AI Trinity: Data, Hardware, and Algorithms
Exponential Growth of Data
Computational Advances to Handle Big Data
Accessing and Developing Algorithms
What Is AI: Deep Versus Machine Learning
What Is Deep Learning?
Why It Matters
2. More Than Games and Moonshots
AI-First Strategy
Where Deep Learning Excels
Financial Crimes
Manufacturing Performance Optimization
Recommendation Engines
Yield Optimization
Predictive Maintenance
3. Options and Trade-Offs for Enterprises to Consume Artificial Intelligence
SaaS Solutions: Quick but Limited
Cloud AI APIs
Building Custom AI Algorithms
4. Challenges to Delivering Value from Custom AI Development and Engineering Countermeasures
Strategy
Technology
Operations
AnalyticOps
Model Transparency
The Move to Autonomous Decisions
Data
Talent
Conclusion
5. Artificial Intelligence Case Studies
Fighting Fraud by Using Deep Learning
Mining Image Data to Increase Productivity
Deep Learning for Image Recognition
Natural-Language Processing for Customer Service
Deep Learning for Document Automation
Conclusion
6. Danske Bank Case Study Details
The Project, the Tools, and the Team
Getting the Right Data in Place
Ensemble Modeling and Champion/Challenger
Working with the Past, Building the Future
Moving the ML Models into Live Production
From Machine Learning to Deep Learning
Visualizing Fraud
Visualizing and Interpreting Deep Learning Models
A Platform for the Future
7. Predictions Through 2020
Strategy
Technology
Operations
Data
Talent
What’s Next
8. Conclusion
Identify High-Impact Business Outcomes
Assess Current Capabilities
Build Out Capabilities
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