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AI & Data Literacy

AI & Data Literacy

By : Bill Schmarzo
4.8 (25)
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AI & Data Literacy

AI & Data Literacy

4.8 (25)
By: Bill Schmarzo

Overview of this book

AI is undoubtedly a game-changing tool with immense potential to improve human life. This book aims to empower you as a Citizen of Data Science, covering the privacy, ethics, and theoretical concepts you’ll need to exploit to thrive amid the current and future developments in the AI landscape. We'll explore AI's inner workings, user intent, and the critical role of the AI utility function while also briefly touching on statistics and prediction to build decision models that leverage AI and data for highly informed, more accurate, and less risky decisions. Additionally, we'll discuss how organizations of all sizes can leverage AI and data to engineer or create value. We'll establish why economies of learning are more powerful than the economies of scale in a digital-centric world. Ethics and personal/organizational empowerment in the context of AI will also be addressed. Lastly, we'll delve into ChatGPT and the role of Large Language Models (LLMs), preparing you for the growing importance of Generative AI. By the end of the book, you'll have a deeper understanding of AI and how best to leverage it and thrive alongside it.
Table of Contents (14 chapters)
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12
Other Books You May Enjoy
13
Index

3 Analytics Literacy

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Before you read this chapter, just some advice – you may never be asked to program a neural network or an unsupervised machine learning algorithm, but it is essential that you have a rough idea as to how these algorithms work and what these algorithms are good at doing. The goal of these next few pages is to demystify data science and these different algorithms so that everyone of every age is prepared to have an everyday analytics conversation.AI and analytics literacy is understanding how advanced analytic algorithms and concepts work – including machine learning, reinforcement learning, and deep learning – and what types of problems these analytical algorithms can be applied to. This is the most challenging chapter of the book as it will provide a broad overview of the different types of advanced analytic algorithms and concepts. Think of this as a family of additional...

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