Practical Linear Algebra for Data Science 1 / converted Edition Mike. Cohen

Practical Linear Algebra for Data Science 1 / converted Edition Mike. Cohen – Ebook Instant Download/Delivery ISBN(s): 9781098120610, 1098120612

Product details:

• ISBN 10: 1098120612
• ISBN 13: 9781098120610
• Author: MIKE. COHEN

If you want to work in any computational or technical field, you need to understand linear algebra. As the study of matrices and operations acting upon them, linear algebra is the mathematical basis of nearly all algorithms and analyses implemented in computers. But the way it’s presented in decades-old textbooks is much different from how professionals use linear algebra today to solve real-world modern applications.

This practical guide from Mike X Cohen teaches the core concepts of linear algebra as implemented in Python, including how they’re used in data science, machine learning, deep learning, computational simulations, and biomedical data processing applications. Armed with knowledge from this book, you’ll be able to understand, implement, and adapt myriad modern analysis methods and algorithms.

Table contents:

1. Introduction

2. Vectors, Part 1

3. Vectors, Part 2

4. Vector Applications

5. Matrices, Part 1

6. Matrices, Part 2

7. Matrix Applications

8. Matrix Inverse

9. Orthogonal Matrices and QR Decomposition

10. Row Reduction and LU Decomposition

11. General Linear Models and Least Squares

12. Least Squares Applications

13. Eigendecomposition

14. Singular Value Decomposition

15. Eigendecomposition and SVD Applications

16. Python Tutorial

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