How to do padding using keras?

This recipe helps you do padding using keras

Recipe Objective

How to do padding using keras? Padding is a parameter that is used to control the number of features at the output with respect to input featues.

Step 1- Importing Libraries.

import keras from keras.models import Sequential from keras.layers import Dense from keras.layers import Dropout from tensorflow.keras import layers

Step 2-Creating a sample input.

We will create a sample input to show the working of the model.

sample_data = [[1, 2, 3, 4],[5, 6, 7, 86, 985],[8, 92, 92837, 7591, 251638, 29386, 188361],] output = keras.preprocessing.sequence.pad_sequences( inputs, padding="post" ) print(output)
[[     1      2      3      4      0      0      0]
 [     5      6      7     86    985      0      0]
 [     8     92  92837   7591 251638  29386 188361]]

What Users are saying..

profile image

Abhinav Agarwal

Graduate Student at Northwestern University
linkedin profile url

I come from Northwestern University, which is ranked 9th in the US. Although the high-quality academics at school taught me all the basics I needed, obtaining practical experience was a challenge.... Read More

Relevant Projects

Isolation Forest Model and LOF for Anomaly Detection in Python
Credit Card Fraud Detection Project - Build an Isolation Forest Model and Local Outlier Factor (LOF) in Python to identify fraudulent credit card transactions.

Time Series Forecasting Project-Building ARIMA Model in Python
Build a time series ARIMA model in Python to forecast the use of arrival rate density to support staffing decisions at call centres.

Learn How to Build PyTorch Neural Networks from Scratch
In this deep learning project, you will learn how to build PyTorch neural networks from scratch.

Build a CNN Model with PyTorch for Image Classification
In this deep learning project, you will learn how to build an Image Classification Model using PyTorch CNN

Ecommerce product reviews - Pairwise ranking and sentiment analysis
This project analyzes a dataset containing ecommerce product reviews. The goal is to use machine learning models to perform sentiment analysis on product reviews and rank them based on relevance. Reviews play a key role in product recommendation systems.

Build ARCH and GARCH Models in Time Series using Python
In this Project we will build an ARCH and a GARCH model using Python

Build a Multi ClassText Classification Model using Naive Bayes
Implement the Naive Bayes Algorithm to build a multi class text classification model in Python.

Build a Text Classification Model with Attention Mechanism NLP
In this NLP Project, you will learn to build a multi class text classification model with attention mechanism.

MLOps Project to Deploy Resume Parser Model on Paperspace
In this MLOps project, you will learn how to deploy a Resume Parser Streamlit Application on Paperspace Private Cloud.

Learn How to Build a Linear Regression Model in PyTorch
In this Machine Learning Project, you will learn how to build a simple linear regression model in PyTorch to predict the number of days subscribed.