Showing results for "Digital Systems" in Computer Science

Machine learning systems are both complex and unique. Complex because they consist of many different components and involve many different stakeholders. Unique because they're data dependent, with data varying wildly from one use case to the next. In this book, you'll learn a holistic approach to designing ML systems that are reliable, scalable, maintainable, and adaptive to changing environments and business requirements. Author Chip Huyen, cofounder of Claypot AI, considers each design decision in the context of how it can help your system as a whole achieve its objectives.

A decade ago, developers built information-sharing software by writing a lot of custom code in a single code base, then adding layers of caching. Now we build information systems: interdependent software and services, data platforms, and event streams. Many of our software-to-systems initiatives fail, though, and when they do, we double down on traditional linear approaches. But linear thinking cannot resolve systems challenges. We need to shift to systems thinking.

The confluence of four technologies - elastic cloud computing, big data, artificial intelligence, and the internet of things - writes Siebel, is fundamentally changing how business and government will operate in the 21st century. Siebel masterfully guides listeners through a fascinating discussion of the game-changing technologies driving digital transformation and provides a roadmap to seize them as a strategic opportunity.

As artificial intelligence reshapes the workplace, you face an unprecedented challenge—one this book transforms into an extraordinary opportunity! Whether you're anxious about your future, struggling to harness AI’s potential, leading teams through change, or preparing to become a Human-AI Coach, Dr. Jon Finn reveals a groundbreaking “first principles” approach to supercharging human cognitive performance—just as sports science revolutionized world-champion athletes' physical abilities.