In the previous chapters, we have become familiar with instantiating NumPy arrays, pandas data frames/series, and performing some basic data manipulation tasks using those. However, a typical data analysis task would involve a more detailed exploration, which in turn requires us to perform more scientific tasks.
This chapter discusses the solution of matrix-oriented problems in SciPy, which constitute the fundamentals of much of the work done in scientific computing and data analysis.
In order to understand the need for learning matrix analysis and linear algebra further, let us look into a few examples:
- Image analysis: Essentially, one can consider an image a matrix with m rows and n columns. In any type of image analysis, such as image classification or transformation, we can potentially work on the image by first converting it into a matrix format and then performing...
