Gated recurrent unit - Learn Data Science with Travis

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...

Unlocking Sequential Intelligence: The Power and Efficiency of Gated Recurrent Units in Deep…

Python in Plain English

Unlocking Sequential Intelligence: The Power and Efficiency of Gated Recurrent Units in Deep Learning Abstract Context: Gated Recurrent Units (GRU) has emerged as a formidable architecture within the...

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…

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…

[NIPS 2017/Part 1] Gated Recurrent Convolution NN for OCR with Interactive Code [ Manual Back Prop…

Towards Data Science

So this is the first part of implementing Gated Recurrent Convolutional Neural Network. And I will cover one by one, so for today lets implement a simple Recurrent Convolutional Neural Network as a…

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...

Quantum Gates

Analytics Vidhya

As introduced in the previous articles, gates can be considered as operations on qubits that change their state from one to another. Since we represent our qubit states as vectors, we can consider…

null recurrent = zero utility?

R-bloggers

The stability result that the ratio converges holds for a Harris π-null-recurrent Markov chain for all functions f,g in L¹(π) [Meyn & Tweedie, 1993, Theorem 17.3.2] is rather fascinating. However, it ...

Understanding GRU Networks

Towards Data Science

In this article, I will try to give a fairly simple and understandable explanation of one really fascinating type of neural network. Introduced by Cho, et al. in 2014, GRU (Gated Recurrent Unit) aims…...

Modern Recurrent Neural Networks

Dive intro Deep Learning Book

The previous chapter introduced the key ideas behind recurrent neural networks (RNNs). However, just as with convolutional neural networks, there has been a tremendous amount of innovation in RNN arch...

Guide to Custom Recurrent Modeling in Keras

Towards Data Science

The initial set of layers for recurrent neural operations universally begins with LSTM, GRU and RNN. But with an increase in the complexity of the task, we should use more complex models. That said…