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1
Introduction
2
Motivation
3
Machine Translation
4
Transformer
5
TensorFlow
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Tensor2Tensor
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Training
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Open Source
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Collaboration
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Papers
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How does it work
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Translation
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Speech Recognition
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Transformer Models
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Image Transformer
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MultiGPU
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Cloud TPU Pod
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Tuning hyper parameters
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Mesh tensor flow
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Importing data
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Problem class
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Models
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Subclasses
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Research subdirectory
25
Looking Ahead
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Mesh
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Image Generation
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Slice Back
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Build Every Tensor
30
Model Layout
31
Model Transformer
32
GitHub
Description:
Explore the powerful Tensor2Tensor library in this 39-minute conference talk from the O'Reilly AI Conference in San Francisco. Dive into the world of deep learning models and datasets, learning how to create state-of-the-art models for various machine learning applications such as translation, parsing, and image captioning. Discover how Tensor2Tensor accelerates the exploration of new ideas in the field. Gain insights into machine translation, speech recognition, and image transformation using Transformer models. Understand the benefits of MultiGPU and Cloud TPU Pod for training. Learn about tuning hyperparameters, importing data, and working with problem classes and models. Explore the research subdirectory and get a glimpse of future developments in mesh tensor flow and image generation. By the end of this talk, you'll have a comprehensive understanding of Tensor2Tensor's capabilities and how to leverage them in your machine learning projects.

Tensor2Tensor - TensorFlow at O’Reilly AI Conference, San Francisco '18

TensorFlow
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