Building models with tf.text

Robby Neale (Google)

1:40pm–2:20pm Wednesday, October 30, 2019

Location: Great American Ballroom J/K

Core technologies

Average rating:

(2.00, 1 rating)

Level

New to TensorFlow

There are many resources for building models from numeric data, which means processing text had to occur outside the model. Robby Neale walks you through ragged tensors and tf.text, showcasing its text-based ops and explaining how to quickly build a model starting with text input in tf.data.

Prerequisite knowledge

Experience with ML development

What you'll learn

Get comfortable building models with text-based input and know where to look for text-related ops

Robby Neale

Google

Robby Neale is a senior software engineer at Google. He leads the tf.text effort on the NLX infrastructure team, focusing on expanding the capabilities of the TensorFlow platform to make creation of text-based models easier for developers.

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Comments

Robby Neale | Senior Software Engineer

07/16/2019 12:36pm PDT

Re Nat: Core is automatically added (and is required). For future reference, you can also leave comments/questions on the github repo (https://github.com/tensorflow/text).

Nat Colley |

07/13/2019 4:03am PDT

I just read your post on Medium, but there was no place to add comments or questions. When I get tf.text, do I also need tf core? Is core automatically included as a dependency with pip install tf text?