Jan K. Argasinski

This book provides an innovative exploration into the realm of artificial intelligence (AI) by developing personalities for large language models (LLMs) using psychological principles. Aimed at making AI interactions feel more human-like, the book guides you through the process of applying psychological assessments to AIs, enabling them to exhibit traits such as extraversion, openness, and emotional stability. Perfect for developers, researchers, and entrepreneurs, this work merges psychology, philosophy, business, and cutting-edge computing to enhance how AIs understand and engage with humans across various industries like gaming and healthcare. The book not only unpacks the theoretical aspects of these advancements but also equips you with practical coding exercises and Python code examples, helping you create AI systems that are both innovative and relatable. Whether you’re looking to deepen your understanding of AI personalities or integrate them into commercial applications, this book offers the tools and insights needed to pioneer this exciting frontier.

This textbook provides semester-length coverage of pattern recognition/classification, accessible to everyone who would like to understand how pattern recognition and machine learning works. It explores the most commonly used classification methods in an intelligible way. Unlike other books available for this course, this one explains from top to bottom each method with all needed details. Every method described is explained with examples in Python. The presentation is designed to be highly accessible to students from a variety of disciplines, with no experience in machine learning. Each chapter contains easy to understand code samples, as well as exercises to consolidate and test knowledge.