Mathematics for Computer Science
This book covers elementary discrete mathematics for computer science and engineering. It emphasizes mathematical definitions and proofs as well as applicable methods.
Bayesian Reasoning and Machine Learning
The book is designed to appeal to students with only a modest mathematical background in undergraduate calculus and linear algebra. No formal computer science or statistical background is required to follow the book, although a basic familiarity with probability, calculus and linear algebra would be useful.
The Promotional Merchandise Handbook
The Promotional Merchandise Handbook is a quick guide to the promotional industry and where branded merchandise fits into the marketing communications mix. The book covers a checklist of what to consider when using marketing gifts and provides useful market research information.
Algorithms for Clustering Data
This book will be useful for those in the scientific community who gather data and seek tools for analyzing and interpreting data. It will be a valuable reference for scientists in a variety of disciplines and can serve as a textbook for a graduate course in exploratory data analysis as well as a supplemental text in courses on research methodology, pattern recognition, image processing, and re-mote sensing.
An Introduction to Functional Programming Through Lambda Calculus
This book encourages learning by abstraction from concrete examples, of understanding calculus through actually ‘doing’ it in an explicitly operational manner, and of gaining oversight of the layers between a simple, foundational system and a rich language of variegated constructs and structures.
Operating Systems: Three Easy Pieces
The book is centered around three conceptual pieces that are fundamental to operating systems: virtualization, concurrency, and persistence. In understanding the conceptual, you will also learn the practical, including how an operating system does things like schedule the CPU, manage memory, and store files persistently. The title is an homage to one of the greatest sets of lecture notes ever created, by one Richard Feynman on the topic of Physics.