How to find the Rank of a Matrix?

How to find the Rank of a Matrix?

How to find the Rank of a Matrix?

This recipe helps you find the Rank of a Matrix


Recipe Objective

Finding the Rank of a matrix manually isn"t a time taking process. So have you tried to do it in python.

So this is the recipe on how we can find the Rank of a Matrix.

Step 1 - Loading Library

We have imported numpy which is needed. import numpy as np

Step 2 - Creating a Matrix

We have created a matrix by using np.array with different values in it. matrixA = np.array([[1, 2, 3, 23], [4, 5, 6, 25], [7, 8, 9, 28], [10, 11, 12, 41]])

Step 3 - Calculating Rank

We have calculated rank of the matrix by using numpy function np.linalg.matrix_rank and passing the matrix through it. print("The Rank of a Matrix: ", np.linalg.matrix_rank(matrixA)) So the output comes as

The Rank of a Matrix:  3

Relevant Projects

Time Series Forecasting with LSTM Neural Network Python
Deep Learning Project- Learn to apply deep learning paradigm to forecast univariate time series data.

Ensemble Machine Learning Project - All State Insurance Claims Severity Prediction
In this ensemble machine learning project, we will predict what kind of claims an insurance company will get. This is implemented in python using ensemble machine learning algorithms.

Learn to prepare data for your next machine learning project
Text data requires special preparation before you can start using it for any machine learning project.In this ML project, you will learn about applying Machine Learning models to create classifiers and learn how to make sense of textual data.

Build an Image Classifier for Plant Species Identification
In this machine learning project, we will use binary leaf images and extracted features, including shape, margin, and texture to accurately identify plant species using different benchmark classification techniques.

Solving Multiple Classification use cases Using H2O
In this project, we are going to talk about H2O and functionality in terms of building Machine Learning models.

Data Science Project - Instacart Market Basket Analysis
Data Science Project - Build a recommendation engine which will predict the products to be purchased by an Instacart consumer again.

Customer Market Basket Analysis using Apriori and Fpgrowth algorithms
In this data science project, you will learn how to perform market basket analysis with the application of Apriori and FP growth algorithms based on the concept of association rule learning.

Data Science Project in Python on BigMart Sales Prediction
The goal of this data science project is to build a predictive model and find out the sales of each product at a given Big Mart store.

Human Activity Recognition Using Smartphones Data Set
In this deep learning project, you will build a classification system where to precisely identify human fitness activities.

Natural language processing Chatbot application using NLTK for text classification
In this NLP AI application, we build the core conversational engine for a chatbot. We use the popular NLTK text classification library to achieve this.