T2T: Creating Sequence to Sequence Models for Generalized Learning Training Course

Overview

Tensor2Tensor (T2T) is a modular, extensible library for training AI models in different tasks, using different types of training data, for example: image recognition, translation, parsing, image captioning, and speech recognition. It is maintained by the Google Brain team.

In this instructor-led, live training, participants will learn how to prepare a deep-learning model to resolve multiple tasks.

By the end of this training, participants will be able to:

  • Install tensor2tensor, select a data set, and train and evaluate an AI model
  • Customize a development environment using the tools and components included in Tensor2Tensor
  • Create and use a single model to concurrently learn a number of tasks from multiple domains
  • Use the model to learn from tasks with a large amount of training data and apply that knowledge to tasks where data is limited
  • Obtain satisfactory processing results using a single GPU

Audience

  • Developers
  • Data scientists

Format of the course

  • Part lecture, part discussion, exercises and heavy hands-on practice

Requirements

  • Hands-on experience with Deep Learning machine learning models

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