Category: Mathematics for Data Science

A transpose of a matrix is obtained by interchanging all its rows into columns or columns into rows. It is denoted by \(\displaystyle {{A}^{t}}\) or \(\displaystyle {{A}^{‘}}\). For example, …

The product of two matrices A and B will be possible if the number of columns of a Matrix A is equal to the number of rows of another …

Matrix Addition and Subtraction in Python programming language is performed like the normal algebraic operations. Before discussing these operations, it is necessary to introduce a bit about Algebra which …

Linear Algebra in TensorFlow: TensorFlow is open source software under Apache Open Source license for dataflow which is frequently being used for machine learning applications like deep-neural-network to improve …

Arrays in python, are frequently used to work with scalars, vectors and matrices, a topic of today’s post. This post is continuation of linear algebra for data science. We …

Linear Algebra for Data Science and machine learning is very essential as the concepts of linear algebra are used to understand the working of algorithms. In this post, we …