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Liquid Software
- How to Achieve Trusted Continuous Updates in the DevOps World
- Narrado por: Steve Spencer
- Duración: 5 h y 8 m
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Resumen del Editor
Software affects everything in our lives.
Imagine that software could be constantly updated without our involvement! No need to figure out hardware specifications. Nothing to interrupt our digital activities. No waiting for lengthy downloads and reboots. What if it all just happened in the background and we could simply enjoy the benefits?
Liquid Software explores a future in which developers code high-quality applications that securely flow to end users with zero downtime. The authors bring insights from their more than 50 years of collective experience in building software in modern development environments. They explain that what sounds like software Utopia is possible and practical!
We’re at the dawn of the next great leap forward in computing - the achievement of continuous software updates.
The liquid software revolution has begun!
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- Versión completa
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General4 out of 5 stars 68
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Narración:4 out of 5 stars 58
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Historia4 out of 5 stars 55
The best-selling author of Big Data is back, this time with a unique and in-depth insight into how specific companies use big data. Big data is on the tip of everyone's tongue. Everyone understands its power and importance, but many fail to grasp the actionable steps and resources required to utilise it effectively. This book fills the knowledge gap by showing how major companies are using big data every day, from an up-close, on-the-ground perspective.
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2 out of 5 stars
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Good book for managers
- De Capnbody en 01-08-18
De: Bernard Marr
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What to Do When Machines Do Everything
- How to Get Ahead in a World of AI, Algorithms, Bots, and Big Data
- De: Malcolm Frank, Paul Roehrig, Ben Pring
- Narrado por: Eric Jason Martin
- Duración: 7 h y 28 m
- Versión completa
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General4.5 out of 5 stars 267
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Narración:4.5 out of 5 stars 236
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Historia4.5 out of 5 stars 235
What to Do When Machines Do Everything is a guidebook to succeeding in the next generation of the digital economy. When systems running on artificial intelligence can drive our cars, diagnose medical patients, and manage our finances more effectively than humans, it raises profound questions on the future of work and how companies compete.
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2 out of 5 stars
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Assumes that machine learning will grow very slow
- De Nathan Burnham en 05-06-17
De: Malcolm Frank, y otros