Practical Discrete Mathematics: Discover math principles that fuel algorithms for computer science and machine learning with Python

Table of Contents

1. Key Concepts, Notation, Set Theory, Relations, and Functions
2. Formal Logic and Constructing Mathematical Proofs
3. Computing with Base-n Numbers
4. Combinatorics Using SciPy
5. Elements of Discrete Probability
6. Computational Algorithms in Linear Algebra
7. Computational Requirements for Algorithms
8. Storage and Feature Extraction of Graphs, Trees, and Networks
9. Searching Data Structures and Finding Shortest Paths
10. Regression Analysis with NumPy and Scikit-Learn
11. Web Searches with PageRank
12. Principal Component Analysis with Scikit-Learn