THE TRANSFORMER’S

Encoder-Decoder

Understanding The Model Architecture

In 2017, Vaswani et al. published a paper titled “Attention Is All You Need” for the NeurIPS conference. They introduced the original transformer architecture for machine translation, performing better and faster than RNN encoder-decoder models, which were mainstream.

Founder & CEO @ kikaben.com | C++, PyTorch | Machine Intelligence Enthusiast | twitter.com/naokishibuya

Love podcasts or audiobooks? Learn on the go with our new app.

Recommended from Medium

Why Boosting Works

Image by author

Introduction to Image Processing — Part 3: Spatial Filtering and Morphological Operations

Markov chain Monte Carlo — Gibbs Sampling for DNA sequence alignment

Addressing Customer Churn With Machine Learning

How Neural Networks process input data

Intuition, Learning and Neural Networks. – mc.ai

Scatter correction and outlier detection in NIR spectroscopy

A Gentle Introduction to Batch Processing in Keras

A BRIEF INTRODUCTION TO MACHINE LEARNING

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store
Naoki

Naoki

Founder & CEO @ kikaben.com | C++, PyTorch | Machine Intelligence Enthusiast | twitter.com/naokishibuya

More from Medium

Draw the Desire: Bringing the sketches to life using Deep Learning

Two Simple Ways To Measure Your Model’s Uncertainty

Paper Review: Denoising Diffusion Probabilistic Models

Less is More: Understanding Neural Network Decisions via Simplified Yet Informative Inputs