DATA MUNGING
DATA CLEANING PYTHON
MACHINE LEARNING RECIPES
PANDAS CHEATSHEET
ALL TAGS
# How to Divide each element of a matrix by a numerical value?

# How to Divide each element of a matrix by a numerical value?

This recipe helps you Divide each element of a matrix by a numerical value

Have to tried to do any mathematical function on all the values of a feature. Doing it manually may be a hectic work.

So this is the recipe on how we can divide each element of a matrix by a numerical value.

```
import numpy as np
```

We have only imported numpy which is needed.

We have created a matrix on which we will perform the operation.
```
matrixA = np.array([[2, 3, 23],
[5, 6, 25],
[8, 9, 28]])
```

First we have created a lambda function which is just like loop as it will iterate the function assined to it to the all elements. Then we have converted the martix into a vector form and finally we have passed the matrix in the function.
```
add_100 = lambda i: i / 9
vectorized_add_100 = np.vectorize(add_100)
print(vectorized_add_100(matrixA))
```

So the output comes as

[[0.22222222 0.33333333 2.55555556] [0.55555556 0.66666667 2.77777778] [0.88888889 1. 3.11111111]]

**
Download Materials
**

Deep Learning Project to implement an Abstractive Text Summarizer using Google's Transformers-BART Model to generate news article headlines.

Data Science Project in Python- Given his or her job role, predict employee access needs using amazon employee database.

In this R data science project, we will explore wine dataset to assess red wine quality. The objective of this data science project is to explore which chemical properties will influence the quality of red wines.

In this data science project in R, we are going to talk about subjective segmentation which is a clustering technique to find out product bundles in sales data.

Estimating churners before they discontinue using a product or service is extremely important. In this ML project, you will develop a churn prediction model in telecom to predict customers who are most likely subject to churn.

In this data science project, you will predict borrowers chance of defaulting on credit loans by building a credit score prediction model.

Build your own image similarity application using Python to search and find images of products that are similar to any given product. You will implement the K-Nearest Neighbor algorithm to find products with maximum similarity.

In this machine learning resume parser example we use the popular Spacy NLP python library for OCR and text classification.

Deep Learning Project- Learn to apply deep learning paradigm to forecast univariate time series data.

This data science in python project predicts if a loan should be given to an applicant or not. We predict if the customer is eligible for loan based on several factors like credit score and past history.