Practical Discrete Mathematics
Discrete math deals with studying finite and distinct elements. With this book, you’ll learn the discrete math language and methods crucial to studying and describing objects and functions in computer science. You'll also focus on the mathematics of machine learning and computer science and prepare to understand real-world algorithm development.
Offered by
Difficulty Level
Intermediate
Completion Time
11h
Language
English
About Book
Who Is This Book For?
This book is for computer scientists looking to expand their knowledge of discrete math, the core topic of their field. University students looking to get hands-on with computer science, mathematics, statistics, engineering, or related disciplines will also find this book useful. Basic Python programming skills and knowledge of elementary real-number algebra are required to get started with this book.
Practical Discrete Mathematics
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 11h total length
Key Concepts, Notation, Set Theory, Relations, and Functions
Formal Logic and Constructing Mathematical Proofs
Computing with Base-n Numbers
Combinatorics Using SciPy
Elements of Discrete Probability
Computational Algorithms in Linear Algebra
Computational Requirements for Algorithms
Storage and Feature Extraction of Graphs, Trees, and Networks
Searching Data Structures and Finding Shortest Paths
Regression Analysis with NumPy and Scikit-Learn
Web Searches with PageRank
Principal Component Analysis with Scikit-Learn
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