Cutting through the mass of technical literature on machine learning and AI and the plethora of fear-mongering books on the rise of killer robots, Secrets of Machine Learning offers a clear-sighted explanation for the informed reader of what this new technology is, what it does, how it works, and why it's so important.
The surge in computer processing power along with the sheer quantities of training data available, means machine learning is now possible in ways wholly unthinkable just five years ago. Computers can recognize potential lung cancer better than doctors, detect fraud better than bankers, and create fake video almost impossible to tell from the real thing. And next, they are likely to drive our cars.
Journalist and news product manager Tom Kohn gets to the heart of the revolutionary new technology that is developing all around us, explaining with precision how the different facets of machine learning work, how companies are using it, and why it is permeating all parts of society right now. The book guides readers through the arcane science and jargon in a clear and understandable way, but is detailed enough that it doesn't gloss over the hard technical concepts.
If you want to know why Siri sometimes misunderstands you, how Netflix recommends your movies, and how machine learning will affect your job — read this book.
Contents:
- About the Author
- Introduction: It's All Just Pixels
- Terminology Unjumbled
- Recommendation Nation
- Search and Seek
- Cool Cats and Hotdogs
- Smile for the Camera
- Drone Swarms and Slaughterbots
- Word Miners
- Lost in Transliteration
- Movement of the Moment
- Roomba Rhumba
- Sensory Overload
- Nation of Workplace Automation
- Image Problem
- Ethics of Data Lakes
- Economist, Forecast Thyself
- Lords of Finance
- Finding Fraud
- Self-Drivers
- Don't Believe the Hyperdrive
- Adversarial Art
- Education, Education, Education
- Social Networking
- Virtual Assistance
- Access Denied
- Wild at Heart
- Generative Generation
- Conclusion
- Further Reading
- Notes and References
- Index
Readership: Pitched at a wide audience, with the educated layperson in mind. It could also be useful to undergraduates who want some idea of where this technology is headed, with an eye toward the workforce. Organizations subject to or involved in machine learning would be appropriate e.g. finance, healthcare, retail, commerce or government technology departments for those who wish to upskill their workers in machine learning.
Key Features:
- Interest in the topic of machine learning has exploded in recent years. Everybody wants to read about artificial intelligence
- The target audience is the educated layperson, rather than computer science professionals or academics. Specifically, those in industries being disrupted by machine learning, or where AI is changing the nature of clerical work and different sectors of the economy
- This book addresses how machine learning affects the futures of the industries it is adopted in, how it works, what its strengths and weaknesses are, what it means for people's lives and livelihoods, and what skills are needed to navigate it
