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The Math Behind Gated Recurrent Units

Towards Data Science

Gated Recurrent Units (GRUs) are a powerful type of recurrent neural network (RNN) designed to handle sequential data efficiently. In this article, we’ll explore what GRUs are, and…

Gated Recurrent Units (GRU)

Dive intro Deep Learning Book

As RNNs and particularly the LSTM architecture ( Section 10.1 ) rapidly gained popularity during the 2010s, a number of papers began to experiment with simplified architectures in hopes of retaining t...

Gated Recurrent Units explained using Matrices: Part 1

Towards Data Science

Often times we get consumed with using Deep learning frameworks that perform all of the required operations needed to build our models. However, there is some value to first understanding some of the…...

Understanding Gated Recurrent Neural Networks

Analytics Vidhya

I strongly recommend to first know how a Recurrent Neural Network algorithm works to get along with this post of Gated RNN’s. Before getting into the details, let us first discuss about the need to…

Deep Dive into Gated Recurrent Units (GRU): Understanding the Math behind RNNs

Towards AI

Gated Recurrent Unit (GRU) is a simplified version of Long Short-Term Memory (LSTM). Let’s see how it works in this article. Photo by Laila Gebhard on Unsplash This article will explain the working o...

Gated Recurrent Units (GRU) — Improving RNNs

Towards Data Science

In this article, I will explore a standard implementation of recurrent neural networks (RNNs): gated recurrent units (GRUs). GRUs were introduced in 2014 by Kyunghyun Cho et al. and are an improvement...

Long Short Term Memory and Gated Recurrent Unit’s Explained — ELI5 Way

Towards Data Science

Hi All, welcome to my blog “Long Short Term Memory and Gated Recurrent Unit’s Explained — ELI5 Way” this is my last blog of the year 2019. My name is Niranjan Kumar and I’m a Senior Consultant Data…

A deep dive into the world of gated Recurrent Neural Networks: LSTM and GRU

Analytics Vidhya

RNNs can further be improved using the gated RNN architecture. LSTM and GRU are some examples of this. The articles explain both the architectures in detail.

LSTM And GRU In Depth

Python in Plain English

Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) are used to handle longer and more complex stories without forgetting the important bits. Long Short-Term Memory (LSTM) * A type of RNN des...

Gated Recurrent Neural Network from Scratch in Julia

Towards AI

Let’s explore Julia to build RNN with GRU cells from zero Image by Author. 1\. Introduction Some time ago, I started learning Julia for scientific programming and data science. The continued adoption...

Recurrent Neural Network Implementation from Scratch

Dive intro Deep Learning Book

We are now ready to implement an RNN from scratch. In particular, we will train this RNN to function as a character-level language model (see Section 9.4 ) and train it on a corpus consisting of the e...

GRU Recurrent Neural Networks — A Smart Way to Predict Sequences in Python

Towards Data Science

A visual explanation of Gated Recurrent Units including an end to end Python example of their use with real-life data Continue reading on Towards Data Science