Course Review: Linear Algebra for Data science by Alison

As I progress in my study of data science, it is only expected that at some point I would endeavour to learn the mathematics behind data science.

I have never studied linear algebra in high school or college, so I have a large learning curve to overcome. Therefore, I decided to take a giant leap forward and take an Alison course on mathematics for data science. The first module of this course is about linear algebra dor data science, so that will be the basis of this review. I also intend to include python code to solve problems in linear algebra because nowadays it is customary that computer programs will solve these problems.

Numpy

NumPy, a Python library for numeric computing, provides a wide range of linear algebra functions for performing various operations on arrays. Some of the functions in numpy that focus on linear algebra are cited below:-

1. numpy.dot(): Computes the dot product of two arrays.
2. numpy.vdot(): Computes the dot product of two arrays in a complex space.
3. numpy.inner(): Computes the inner product of two arrays.
4. numpy.matmul(): Computes the matrix product of two arrays.
5. numpy.linalg.det(): Computes the determinant of an array.