This course gives you a synopsis of the encoder-decoder architecture, which is a powerful and prevalent machine learning architecture for sequence-to-sequence tasks such as machine translation, text summarization, and question answering. You learn about the main components of the encoder-decoder architecture and how to train and serve these models. In the corresponding lab walkthrough, you’ll code a simple implementation of the encoder-decoder architecture in TensorFlow.
Encoder-Decoder Architecture with Google Cloud
Free Course
Learn about the main components of the encoder-decoder architecture and how to train and serve these models.
Estimated time
Approx. 1 Hour
Skill level
Intermediate
Prerequisites
See prerequisites in detail
In collaboration with
About this course
What you will learn
Encoder-Decoder Architecture with Google Cloud
- Understand the main components of the encoder-decoder architecture.
- Learn how to train and generate text from a model by using the encoder-decoder architecture.
- Learn how to write your own encoder-decoder model in Keras.
Prerequisites and requirements
General experience in Python programming and Tensorflow.
See the Technology Requirements for using Udacity.
Why take this course?
This course covers the essential elements of the encoder-decoder architecture and provides guidance on training and deploying these models. Additionally, during the lab walkthrough, you will have the opportunity to code a basic implementation from scratch of the encoder-decoder architecture for generating poetry using TensorFlow.
Learn with the best.
Google Cloud Training
Built in collaboration with Google Cloud Training