Machine Learning and Artificial Intelligence

About the Book

In today's rapidly evolving world of Al and machine learning, the vast number of models, concepts, and algorithms can feel overwhelming. With so much knowledge scattered across online resources, it's easy to feel lost or stressed about where to start.

Over the past seven and half years, I've focused on gathering and distilling the most important concepts, algorithms, and models into one comprehensive and accessible resource. This book is the result of this effort.

My goal is to make learning both simple and fast, the two pillars of effective education today. To make even the most complex ideas memorable, I've included comics and humorous examples throughout the book with the hope that readers not only understand the material but also retain it long after they've finished reading.

About the Author

Reza Rawassizadeh is an Associate Professor of Computer Science at Boston University with over a decade of experience in academic research and industrial projects. His scholarly contributions span digital health, ubiquitous technologies, resource-efficient computing, and on-device machine learning. His research emphasizes developing energy-efficient machine learning and Al models tailored for affordable hardware platforms, advancing the democratization of Al.

About the author

Reza Rawassizadeh is a professor of Computer Science at Boston University with over a decade of experience in academic research and industrial projects. His scholarly contributions span digital health, ubiquitous technologies, resource-efficient computing, and on-device machine learning. His research emphasizes developing energy-efficient machine learning and AI models tailored for affordable hardware platforms, advancing the democratization of AI.