Category: 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 …

Machine learning is a subfield of Artificial Intelligence. The concept of machine learning originally started in 1959 by an American Arthur Samuel. He was an expert in the field …

Generally, data is a set of factual information based on numbers, words, observations, measurements that can be used for calculation, discussion and reasoning. The rough dataset is the essential …

Machine Learning is the most famous procedure of foreseeing the future or arranging data to help individuals in settling on essential choices. The algorithms are trained over models through …

In this article we are going to discuss machine learning with python with the help of a real-life example. Before we proceed towards a real-life example, just recap the …