Many modeling, machine learning, and optimization algorithms rely on linear algebra concepts. These concepts include eigenvalues/vectors, matrix multiplication, matrix inversion, and more. Thus, data utilized by data scientists often has to be represented in matrix form, and data scientists will likely need to employ matrix operations in their applications.
- A matrix is a rectangular array representation of numbers, expressions, etc.
- Elements in a matrix are referenced by a row and column index.
gonum.org/v1/gonum/matprovides functionality to create, modify, and manipulate matrices made up of float64 values.
The Matrix Cookbook
Khan Academy - Matrices
Khan Academy - Linear Algebra
gonum.org/v1/mat docs
Form a float64 matrix
Modify a matrix
Access values in a matrix
Format matrix output
Create a matrix from diabetes.csv using gonum.org/v1/gonum/mat. Format and output the first 10 rows to standard out.
All material is licensed under the Apache License Version 2.0, January 2004.