Overview

This course provides a comprehensive overview of the encoder-decoder architecture, a powerful machine learning architecture commonly used for sequence-to-sequence tasks such as machine translation, text summarization, and question answering. Participants will learn about the main components of the encoder-decoder architecture and how to train and serve these models. The course includes a lab walkthrough where participants will code a simple implementation of the encoder-decoder architecture for poetry generation using TensorFlow.

Prerequisites

Participants should have a solid foundation in Python and TensorFlow to fully benefit from this course.

Modules

• Understand the main components of the encoder-decoder architecture.
• Learn how to train and generate text from a model using the encoder-decoder architecture.
• Learn how to write your own encoder-decoder model in Keras.

Price

Most courses offer free access to course materials such as videos and documents. However, labs may require the purchase of an individual subscription or credits. Labs can also be unlocked through participation in campaigns. All required activities in a course must be completed to earn the completion badge.

Course Contents

Interested individuals can explore additional content in their learning path or browse the catalog upon finishing the course. The course is available in multiple languages including English, español (Latinoamérica), français, עברית, bahasa Indonesia, italiano, 日本語, 한국어, português (Brasil), 简体中文, and 繁體中文.

Participants can also take this course with authorized on-demand partners such as Coursera and Pluralsight. For those who prefer learning with an instructor, the public classroom schedule is available.

What you will get from this course?

Upon completion of the course, participants can earn a badge of completion to showcase their newly acquired skills. Badges can be shared on social networks to boost one's cloud career.