How to ADD numerical value to each element of a matrix?

How to ADD numerical value to each element of a matrix?

How to ADD numerical value to each element of a matrix?

This recipe helps you ADD numerical value to each element of a matrix

In [1]:
## How to ADD numerical value to each electment of a matrix
def Kickstarter_Example_15():
    print(format('How to add a constant to each electment of a matrix',

    # Load library
    import numpy as np

    # Create two vectors
    matrixA = np.array([[2, 3, 23],
                       [5, 6, 25],
                       [8, 9, 28]])

    # Create a function that adds 100 to something
    add_100 = lambda i: i + 100

    # Create a vectorized function
    vectorized_add_100 = np.vectorize(add_100)

    # Apply function to all elements in matrix
    print(); print(vectorized_add_100(matrixA))

**********How to add a constant to each electment of a matrix***********

[[102 103 123]
 [105 106 125]
 [108 109 128]]

Relevant Projects

Zillow’s Home Value Prediction (Zestimate)
Data Science Project in R -Build a machine learning algorithm to predict the future sale prices of homes.

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-TalkingData AdTracking Fraud Detection
Machine Learning Project in R-Detect fraudulent click traffic for mobile app ads using R data science programming language.

Music Recommendation System Project using Python and R
Machine Learning Project - Work with KKBOX's Music Recommendation System dataset to build the best music recommendation engine.

German Credit Dataset Analysis to Classify Loan Applications
In this data science project, you will work with German credit dataset using classification techniques like Decision Tree, Neural Networks etc to classify loan applications using R.

Anomaly Detection Using Deep Learning and Autoencoders
Deep Learning Project- Learn about implementation of a machine learning algorithm using autoencoders for anomaly detection.

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.

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

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.

Machine Learning or Predictive Models in IoT - Energy Prediction Use Case
In this machine learning and IoT project, we are going to test out the experimental data using various predictive models and train the models and break the energy usage.