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Demystifying Artificial Intelligence
This book is intended for business professionals that want to understand the fundamental concepts of Artificial Intelligence, their applications and limitations. Built as a collaborative effort between academia and the industry, this book bridges the gap between theory and business application, demystifying AI through fundamental concepts and industry examples. The reader will find here an overview of the different AI techniques to search, plan, reason, learn, adapt, understand and interact. The book covers the two traditional paradigms in AI: the statistical and data-driven AI systems, which learn and perform by ingesting millions of data points into machine learning algorithms, and the consciously modelled AI systems, known as symbolic AI systems, which use explicit symbols to represent the world and make conclusions. Rather than opposing those two paradigms, the book will also show how those different fields can complement each other. All royalties go to a charity. "Demystifying AI reveals its true power: not as a mysterious force, but as a tool for human progress, accessible to all who seek to understand it." Dr. Barak Chizi, Chief Data & Analytics Officer, KBC Group
Demystifying Artificial Intelligence
Readable as a whole or by chapter, this book is intended for business practitioners that have a bachelor or master's degree outside of the field of computer science or AI but still want to go deeper in their understanding of the AI technologies, their applicability and limitations. Such reading can also be useful as a general introduction for students taking an MBA class, or similar. The reader will find in this book a solid overview of the different AI technologies supporting systems that search, plan, reason, learn, adapt, understand or interact. All these terms are demystified in the book. The book covers the two traditional paradigms in AI: on one side, data-driven AI systems, that learn...
Model-Based Machine Learning
Today, machine learning is being applied to a growing variety of problems in a bewildering variety of domains. A fundamental challenge when using machine learning is connecting the abstract mathematics of a machine learning technique to a concrete, real world problem. This book tackles this challenge through model-based machine learning which focuses on understanding the assumptions encoded in a machine learning system and their corresponding impact on the behaviour of the system. The key ideas of model-based machine learning are introduced through a series of case studies involving real-world applications. Case studies play a central role because it is only in the context of applications th...
MPLS and VPN Architectures
A practical guide to understanding, designing, and deploying MPLS and MPLS-enabled VPNs In-depth analysis of the Multiprotocol Label Switching (MPLS) architecture Detailed discussion of the mechanisms and features that constitute the architecture Learn how MPLS scales to support tens of thousands of VPNs Extensive case studies guide you through the design and deployment of real-world MPLS/VPN networks Configuration examples and guidelines assist in configuring MPLS on Cisco(R) devices Design and implementation options help you build various VPN topologies Multiprotocol Label Switching (MPLS) is an innovative technique for high-performance packet forwarding. There are many uses for this new t...
Generative AI and LLMs
Generative artificial intelligence (GAI) and large language models (LLM) are machine learning algorithms that operate in an unsupervised or semi-supervised manner. These algorithms leverage pre-existing content, such as text, photos, audio, video, and code, to generate novel content. The primary objective is to produce authentic and novel material. In addition, there exists an absence of constraints on the quantity of novel material that they are capable of generating. New material can be generated through the utilization of Application Programming Interfaces (APIs) or natural language interfaces, such as the ChatGPT developed by Open AI and Bard developed by Google. The field of generative ...
Who's who of Southern Africa
Vols. for 1967-70 include as a section: Who's who of Rhodesia, Mauritius, Central and East Africa.
Books Abroad
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Le figaro magazine
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