At MentorCruise, we are all about making the most out of the experience of others. As part of that, we've connected and asked dozens of experts and professionals about their favourite Artificial Intelligence books – and here are the answers.
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Understanding the concepts of Artificial Intelligence starts with understanding the fundamentals. On your way to mastery, it's crucial for you to understand how certain concepts were derived, and why things work like they do. Starting with these resources is the best way to do so.
What is AI 2041 about? AI 2041 (2021) is a provocative work of speculative fiction with analysis that explores the ways in which AI will shake up our world over the next twenty years. We're just at the beginning of the technological revolution that AI will bring.
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AI Superpowers by Kai-Fu Lee is a thought-provoking book that explores the future of AI. It highlights the rise of China as an AI powerhouse, the potential job displacement, and how we can navigate the complex ethical implications of this technology.
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The Singularity Is Near' by Ray Kurzweil predicts that exponential growth of technology will result in a singularity, where humans merge with machines to become super intelligent beings. It raises ethical and social implications.
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Human Compatible: Artificial Intelligence and the Problem of Control is a 2019 non-fiction book by computer scientist Stuart J. Russell. It asserts that the risk to humanity from advanced artificial intelligence is a serious concern despite the uncertainty surrounding future progress in AI.
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When we're talking about computer science, however, pattern recognition is the technology that matches incoming data with information stored in a database. Thus, pattern recognition is a type of machine learning since it uses machine learning algorithms to recognize patterns.
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“Artificial Intelligence: A Modern Approach” goes beyond the basics and delves into advanced topics in AI. It covers natural language processing, an area concerned with enabling computers to understand and generate human language. The book explores techniques for parsing, semantic analysis, and machine translation.
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These books are not required for you to learn Artificial Intelligence, but they are highly recommended for you to deepen your knowledge.
Baum argues that the complexity of mind is the outcome of evolution, which has built thought processes that act unlike the standard algorithms of computer science and that to understand the mind we need to understand these thought processes and the evolutionary process that produced them in computational terms.
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At 100 pages (or a little more), the book is short enough to read in a single sitting. Yet, despite its length, it covers all the major machine learning approaches, ranging from classical linear and logistic regression, through to modern support vector machines, deep learning, boosting, and random forests.
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They argue that the Second Machine Age involves the automation of a lot of cognitive tasks that make humans and software-driven machines substitutes, rather than complements. They contrast this with what they call the "First Machine Age", or Industrial Revolution, which helped make labor and machines complementary.
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This list is curated by MentorCruise and can include Amazon affiliate links. Have any other suggestions? Add here.
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