Linear algebra, which provides the basic theory for utilizing vectors and matrices, provides many algorithms to increase the accuracy and speed of calculations in the computing process for data analysis and to discover the characteristics of the data set. These algorithms are very useful for understanding probability, statistics, and computing applied to learning machines. This book introduces many basic aspects of linear algebra using Python packages such as NumPy and SymPy. Chapters 1 and 2 introduce the creation and characteristics of vectors and matrices. These characteristics are advantageous for various characteristics and calculations of functions by connecting linear functions with vectors or matrices. This part is introduced in Chapter 3. The process of converting a function to another function while maintaining its basic characteristics is covered in Chapter 4. This transformation can convert and apply complex functions to a simpler form. This transformation is called decomposition and is introduced in Chapter 5. In this process, various Python functions and packages are applied and their descriptions are attached in the appendix.

Linear Algebra with Python PDF

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