Introduction to Applied Linear Algebra: Vectors, Matrices, and Least Squares
This book is meant to provide an introduction to vectors, matrices, and least squares methods, basic topics in applied linear algebra. Our goal is to give the beginning student, with little or no prior exposure to linear algebra, a good grounding in the basic ideas, as well as an appreciation for how they are used in many applications.
12-Point Checklist For Building an Online Business
Building an online business is never an easy task. Either if you are a business veteran or a beginner pursuing a dream, there are numerous challenges to overcome, trends to keep an eye on and a need for tremendous preparation.
Foundations of Databases
The database management system is typically accompanied by a large and evergrowing body of application software that accesses and modifies the stored information. The primary focus in this book is to present part of the theory underlying the design and use of these systems.
Mining of Massive Datasets
Mining of Massive Datasets focuses on data mining of very large amounts of data, that is, data so large it does not fit in main memory. This book also takes an algorithmic point of view: data mining is about applying algorithms to data, rather than using data to ‘train’ a machine-learning engine of some sort.
From Algorithms to Z-Scores: Probabilistic and Statistical Modeling in Computer Science
Why is this book different from all other books on mathematical probability and statistics? The key aspect is the book’s consistently applied approach, especially important for engineering students.
Building Blocks for Theoretical Computer Science
This book teaches two different sorts of things, woven together. It teaches you how to read and write mathematical proofs. It provides a survey of basic mathematical objects, notation, and techniques which will be useful in later computer science courses. These include propositional and predicate logic, sets, functions, relations, modular arithmetic, counting, graphs, and trees.