Marcia Kaufman Books

The easy way to understand and implement cloud computing technology written by a team of experts Cloud computing can be difficult to understand at first, but the cost-saving possibilities are great and many companies are getting on board. If you've been put in charge of implementing cloud computing, this straightforward, plain-English guide clears up the confusion and helps you get your plan in place. You'll learn how cloud computing enables you to run a more green IT infrastructure, and access technology-enabled services from the Internet ("in the cloud") without having to understand, manage, or invest in the technology infrastructure that supports them. You'll also find out what you need to consider when implementing a plan, how to handle security issues, and more. Cloud Computing For Dummies gets straight to the point, providing the practical information you need to know.

Discover the next major revolution in data science and AI and how it applies to your organization In Causal Artificial Intelligence: The Next Step in Effective, Efficient, and Practical AI, a team of dedicated tech executives delivers a business-focused approach based on a deep and engaging exploration of the models and data used in causal AI. The book’s discussions include both accessible and understandable technical detail and business context and concepts that frame causal AI in familiar business settings. Useful for both data scientists and business-side professionals, the book offers: Clear and compelling descriptions of the concept of causality and how it can benefit your organization Detailed use cases and examples that vividly demonstrate the value of causality for solving business problems Useful strategies for deciding when to use correlation-based approaches and when to use causal inference An enlightening and easy-to-understand treatment of an essential business topic, Causal Artificial Intelligence is a must-read for data scientists, subject matter experts, and business leaders seeking to familiarize themselves with a rapidly growing area of AI application and research.

This comprehensive guide explores the technologies behind cognitive computing, which harnesses big data to create systems that learn from experience and generate insights. It delves into key components such as knowledge representation, natural language processing, and dynamic learning methods that rely on evidence rather than constant reprogramming. Through detailed case studies from sectors like finance, healthcare, and manufacturing, readers gain practical insights into designing and testing cognitive systems. Contributions from organizations like Cleveland Clinic and Memorial Sloan-Kettering highlight real-world implementations, while a dedicated chapter on the IBM Watson platform underscores its role in shaping the cognitive computing landscape. The book also covers projects from Qualcomm, Hitachi, Google, and Amazon, showcasing the evolution of cognitive solutions that integrate concepts from artificial intelligence and big data analytics. Readers will learn to assess their application portfolios for potential pilot projects and leverage cognitive computing to drive organizational transformation. As cognitive systems emerge as a new computing era, this guide equips professionals with the theoretical and practical knowledge needed to navigate the evolving landscape of human-machine interaction and capitalize on new opportunities in their industries.