Linear Algebra for Data Science & Machine Learning in Python

This course will help you in understanding of the Linear Algebra and math’s behind Data Science and Machine Learning. Linear Algebra is the fundamental part of Data Science and Machine Learning. This course consists of lessons on each topic of Linear Algebra + the code or implementation of the Linear Algebra concepts or topics.

There’re tons of topics in this course. To begin the course:

We have a discussion on what is Linear Algebra and Why we need Linear Algebra
Then we move on to Getting Started with Python, where you will learn all about how to setup the Python environment, so that it’s easy for you to have a hands-on experience.

Then we get to the essence of this course;

Vectors & Operations on Vectors
Matrices & Operations on Matrices
Determinant and Inverse
Solving Systems of Linear Equations
Norms & Basis Vectors
Linear Independence
Matrix Factorization
Orthogonality
Eigenvalues and Eigenvectors
Singular Value Decomposition (SVD)

Again, in each of these sections you will find Python code demos and solved problems apart from the theoretical concepts of Linear Algebra.

You will also learn how to use the Python’s numpy library which contains numerous functions for matrix computations and solving Linear Algebric problems.

So, let’s get started….
Who this course is for:

Anyone who is curious about how Linear Algebra is used in Machine Learning
Anyone who wants to understand Maths and Linear Algebra behind Data Science
Anyone who wants to develop fundamental foundations for deployment of Machine Learning Techniques

Requirements

You should have familiarity with fundamentals of Maths
All the implementation of Linear Algebra concepts are in Python, so familiarity with Python will be an added advantage

1. Introduction	10. Norms	11. Basis Vectors
12. Linear Independence	13. Vector Subspaces	14. Matrix Factorization
15. Orthogonality	16. Eigenvalues and Eigenvectors	17. Single Value Decomposition
18. Least Squares Problem	19. Moore-Penrose Pseudoinverse	2. Getting Started with Python
3. Vectors	4. Operations on Vectors	5. Matrices
6. Operations on Matrices	7. Matrix Determinant and Inverse	8. System of Linear Equations
9. Matrix Equations Ax=b

Nie ma plików w tym folderze