دانلود کتاب Linear Algebra Coding With Python - Python’s Application For Linear Algebra 2020 edition 1

Python is one of the most popular languages ​​for data analysis and prediction. Moreover, Tensorflow and torch, which are useful tools for modern deep learning, are fully implemented by Python. The basic form of data in these languages ​​is the array, which is generated by the important numpy package in Python. In particular, matrices are the foundation of data science because they contain structures of vectors and matrices that give the meaning of the direction and magnitude of each value in the data set. For example, the matrix structure allows transforming into a simple form without losing the basic properties of a huge data set. These transformations are useful for efficient data processing and for finding implicit properties. Linear algebra, a field that provides a basic theory of the usefulness of vectors and matrices, provides several algorithms to increase the accuracy and speed of computation in the computational process of analyzing data and discovering properties of a data set. These algorithms are very useful for understanding the process of calculating probability, statistics, and machine learning. This book introduces many basics of linear algebra using the python packages numpy, sympy, etc. Chapters 1 and 2 introduce the creation and properties of vectors and matrices. Chapter 3 describes the linear system through the process of calculating the solution in a system of simultaneous equations. Space, a concept introduced in Chapter 4, is used to infer the collective properties and relationships of each vector in a linear system. Chapter 5 introduces the coordinate system to represent the linear system geometrically. Chapter 6 introduces the transformation process while preserving basic properties such as vectors and matrices. Finally, Chapter 7 describes several ways to parse the archetype into a simple form. In this process, we use a variety of Python functions.