What is RNN in neural networks

This recipe explains what is RNN in neural networks

Recipe Objective - What is RNN in neural networks?

Recurrent neural networks processes the sequences by iterating through the sequence elements and maintaining the state containing information relative to what it has seen so far usually. It functions just like human brain which contains a biological intelligence which processes the information incrementally while maintaining an internal model of what it’s processing and which is built from past information and constantly updated as new information comes in. RNN is a type of neural networks which consists of internal loop so that network loops internally over sequence elements. The state of the RNN is reset between the processing of two different independent sequences such as two different IMDB reviews so it still consider one sequence as a single data point that is a single input to the network.

This recipe explains what are Recurrent neural networks and how they are executed.

Complete Guide to Tensorflow for Deep Learning with Python for Free

Explanation of recurrent neural network.

In RNN, the information cycles through the loop that is when it makes a decision, it considers the current input and also what it has learned from the inputs it had received previously. In Feed-forward neural networks, it does not have memory of the input they receive and are bad at predicting the coming next as the feed-forward network only considers the current input, it does not have notion of order in time. It don't remember anything about what happened in the past except its training.

Recurrent neural network is mainly a sequence of neural networks that you train one after another with backpropagation. RNN has access to less information than the earlier baseline models in many neural network problems and simple rnn layer is not so good ar processing long sequences such as text.

What Users are saying..

profile image

Savvy Sahai

Data Science Intern, Capgemini
linkedin profile url

As a student looking to break into the field of data engineering and data science, one can get really confused as to which path to take. Very few ways to do it are Google, YouTube, etc. I was one of... Read More

Relevant Projects

Avocado Machine Learning Project Python for Price Prediction
In this ML Project, you will use the Avocado dataset to build a machine learning model to predict the average price of avocado which is continuous in nature based on region and varieties of avocado.

Learn to Build a Polynomial Regression Model from Scratch
In this Machine Learning Regression project, you will learn to build a polynomial regression model to predict points scored by the sports team.

Skip Gram Model Python Implementation for Word Embeddings
Skip-Gram Model word2vec Example -Learn how to implement the skip gram algorithm in NLP for word embeddings on a set of documents.

AWS MLOps Project to Deploy a Classification Model [Banking]
In this AWS MLOps project, you will learn how to deploy a classification model using Flask on AWS.

CycleGAN Implementation for Image-To-Image Translation
In this GAN Deep Learning Project, you will learn how to build an image to image translation model in PyTorch with Cycle GAN.

Loan Eligibility Prediction in Python using H2O.ai
In this loan prediction project you will build predictive models in Python using H2O.ai to predict if an applicant is able to repay the loan or not.

OpenCV Project for Beginners to Learn Computer Vision Basics
In this OpenCV project, you will learn computer vision basics and the fundamentals of OpenCV library using Python.

Text Classification with Transformers-RoBERTa and XLNet Model
In this machine learning project, you will learn how to load, fine tune and evaluate various transformer models for text classification tasks.

Recommender System Machine Learning Project for Beginners-4
Collaborative Filtering Recommender System Project - Comparison of different model based and memory based methods to build recommendation system using collaborative filtering.

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.

OSZAR »