Showing results for "Systems Science" in Programming

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.

Data science happens in code. The ability to write reproducible, robust, scaleable code is key to a data science project's success—and is absolutely essential for those working with production code. This practical book bridges the gap between data science and software engineering, and clearly explains how to apply the best practices from software engineering to data science.

If you're a new or experienced designer of conversational voice first experiences, this handy reference provides actionable answers to key aspects of eyes-busy, hands-busy, voice-only user interfaces. Designed as a companion to books about conversational voice design, this guide includes important details regarding eyes-free, hands-free, voice-only interfaces delivered by Amazon Echo, Google Nest, and a variety of in-car experiences.