datascience.stackexchange.com
Training an RNN with examples of different lengths in Keras
1 min read · · I am trying to get started learning about RNNs and I'm using Keras. I understand the basic premise of vanilla RNN and LSTM layers, but I'm having trouble understanding a certain technical point for · Shared by 4, including Dayyan Smith
peterbloem.nl
Transformers from scratch
20+ min read · · Transformers are a very exciting family of machine learning architectures. Many good tutorials exist (e.g. [1, 2]) but in the last few years, transformers have mostly become simpler, so that it is now… · Shared by 15, including Dayyan Smith
devopedia.org
Attention Mechanism in Neural Networks
~16 min read · · In machine translation, the encoder-decoder architecture is common. The encoder reads a sequence of words and represents it with a high-dimensional real-valued vector. This vector, often called the… · Shared by 4, including Dayyan Smith
lilianweng.github.io
Attention? Attention!
~12 min read · · Attention has been a fairly popular concept and a useful tool in the deep learning community in recent years. In this post, we are gonna look into how attent... · Shared by 13, including Dayyan Smith
Towards Data Science
Attn: Illustrated Attention
~12 min read · · Attention in GIFs and how it is used in machine translation like Google Translate · Shared by 12, including Dr. Ganapathi Pulipaka 🇺🇸, Dayyan Smith
youtube.com
A friendly introduction to Recurrent Neural Networks
· A friendly explanation of how computers predict and generate sequences, based on Recurrent Neural Networks. For a brush up on Neural Networks, check out this... · Shared by 9, including Claudio Perez Gamayo, Dayyan Smith, rohit
sites.google.com
Neural Machine Translation
3 min read · · Welcome to the homepage for our ACL 2016 tutorial, with more information and updated material to supplement the official ACL page! The presenters were Thang Luong @lmthang, Kyunghyun Cho @kchonyc, and… · Shared by 4, including Dayyan Smith
kurious.pub
Illustrated Guide to Recurrent Neural Networks
· Understand the intuition with this illustrated guide to recurrent neural networks · Shared by 4, including Dayyan Smith
karpathy.github.io
The Unreasonable Effectiveness of Recurrent Neural Networks
· Musings of a Computer Scientist. · Shared by 170, including Nils Hitze, Marco Unternaehrer, Rodrigo Sampaio Vaz, Jeff Heuer, Chung Chen, Jens-Christian Fischer, Christopher Allen, Claudio Noguera, Bruno T., Thomas Power, Dayyan Smith, PotHix, Thomas Telandro, Brian, Vasilis Akoinoglou, Nico Müller 🇺🇦, Alexander Seifert, Thomas Spreng, Kenneth Kalmer, Bryan Onel
victorzhou.com
An Introduction to Recurrent Neural Networks for Beginners
~20 min read · · A simple walkthrough of what RNNs are, how they work, and how to build one from scratch in Python. · Shared by 67, including Ines Bieler, 瑞拿頭, Dayyan Smith, Charlie O'Keefe, rohit, Fabrizio Bianchi
Machine Learning Mastery
A Gentle Introduction to RNN Unrolling
5 min read · · Recurrent neural networks are a type of neural network where the outputs from previous time steps are fed as input to the current time step. This creates a network graph or circuit diagram with cycles, which can make it difficult to understand how information moves through the network. In this post, you will discover the … · Shared by 8, including Dayyan Smith, Chung Chen
