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Frontmatter

Contents

Preface

Chapter 1: The Foundations of Artificial Intelligence

Chapter 2: Foundations of Machine Learning

Chapter 3: Deep Learning and Neural Networks

Chapter 4: Natural Language Processing (NLP)

Chapter 5: Computer Vision

Chapter 6: Ethics and Bias in AI

Chapter 7: AI in Practice: Industry Case Studies

Chapter 8: Future of AI and Emerging Technologies

Chapter 9: Getting Started With AI Development

Appendix A: Overview of the Lisp Programming Language

Appendix B: Resources and Community

Index

This book is a guide to navigating the evolving landscape of artificial intelligence. Designed for both novices and seasoned professionals it covers a broad range of topics from fundamental ideas to innovative advancements. Readers will investigate the principles of machine learning, explore the intricacies of deep learning architectures, and discover the applications of natural language processing and computer vision. With its concise explanations and useful examples, it gives readers the knowledge and abilities they need to confidently traverse the changing field of artificial intelligence.

This book is a guide to navigating the evolving landscape of artificial intelligence. Designed for both novices and seasoned professionals it covers a broad...

Format

AI Revealed

Theory, Applications and Ethics

Herman L. Erik

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