SciPy Utilities

Explore how SciPy provides utilities for handling sparse matrices in optimization problems. Understand the characteristics and applications of COO, CSR, and CSC sparse matrix formats and learn how to perform arithmetic operations efficiently using these formats in Python.

We'll cover the following...

Sparse matrices
The COO format
The CSR format
The CSC format

Sparse matrices

A sparse matrix is a matrix in which most of the elements are zero. By contrast, if most of the elements are nonzero, then the matrix is considered dense. The number of zero-valued elements divided by the total number of elements—for example, $m*n$ for an $m × n$ matrix—is called the sparsity of the matrix.

Sparse matrices are incredibly useful in scientific computing, where they can provide significant computational and storage efficiencies. Many large-scale systems give ...

1.Introduction to Optimization

2.Vector Calculus

3.Convex Optimization

4.Gradient Descent for Non-Convex Optimization

Project

5.Constrained Optimization

6.Miscellaneous Methods

7.Course Conclusion

Assessment

Mini Project

SciPy Utilities

Sparse matrices