Showing results for "the world" in Data Science

In industry after industry, data, analytics, and AI-driven processes are transforming the nature of work. While we often still treat AI as the domain of a specific skill, business function, or sector, we have entered a new era in which AI is challenging the very concept of the firm. AI-centric organizations exhibit a new operating architecture, redefining how they create, capture, share, and deliver value.

As the global economic landscape shifts at an increasing rate, it's more important than ever that citizens understand the building blocks of the new world economy. In this lively guide, Randy Charles Epping cuts through the jargon to explain the fundamentals. In 36 engaging chapters, Epping lays bare everything from NGOs and nonprofits to AI and data mining. With a comprehensive glossary and absolutely no graphs, The New World Economy: A Beginner's Guide is essential listening for anyone who wants to understand what is going on in the world around them.

The Big Book of Dashboards presents a comprehensive reference for those tasked with building or overseeing the development of business dashboards. Comprising dozens of examples that address different industries and departments (healthcare, transportation, finance, human resources, marketing, customer service, sports, etc.) and different platforms (print, desktop, tablet, smartphone, and conference room display) The Big Book of Dashboards is the only book that matches great dashboards with real-world business scenarios.

Real-World Machine Learning will teach you the concepts and techniques you need to be a successful machine learning practitioner without overdosing you on abstract theory and complex mathematics. By working through immediately relevant examples in Python, you'll build skills in data acquisition and modeling, classification, and regression. You'll also explore the most important tasks like model validation, optimization, scalability, and real-time streaming. When you're done, you'll be ready to successfully build, deploy, and maintain your own powerful ML systems.

Info We Trust celebrates data storytelling, as explained by one of the field's most talented creators. Both engineer and artist, R. J. Andrews draws on disciplines from across the human experience to show how to create new ways of seeing the world. And most importantly, to build powerful data-driven information that is worthy of trust.

"Big Data" is on the covers of Science, Nature, The Economist, and Wired magazines, on the front pages of the Wall Street Journal and The New York Times. But despite the media hyperbole, as Christine Borgman points out in this examination of data and scholarly research, having the right data is usually better than having more data; little data can be just as valuable as big data. Borgman, an often-cited authority on scholarly communication, argues that data have no value or meaning in isolation; they exist within a knowledge infrastructure.

This book is a scientific expedition to research and explore the enterprise-grade big data appliances with blended OLTP and OLAP capabilities. Enterprise database systems with the aid of big data analytics create an intelligent ecosystem by taming and wrangling the data coming from extreme-disparate sources of structured and unstructured channels with massive parallelization techniques to discover, visualize, predict, and action the patterns and trends of mashups of big data.

Data Science stands at the forefront of innovation in the tech industry, driving profound decisions and revolutionizing the way companies operate. "Ace the Data Science Interview" is your definitive guide to mastering the interview process at the most prestigious tech firms around the globe.