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

TensorFlow via YouTube

Overview

This course aims to teach learners about Tensor2Tensor, a library of deep learning models and datasets that enables the creation of advanced models for various machine learning applications like translation, parsing, and image captioning. The course covers topics such as Machine Translation, Transformer Models, TensorFlow, Training, Open Source Collaboration, and Tuning hyperparameters. The teaching method involves exploring how Tensor2Tensor works, including Transformer Models, Image Transformer, MultiGPU, Cloud TPU Pod, and Mesh tensor flow. This course is intended for individuals interested in deep learning, machine learning, and developing state-of-the-art models for ML applications.

Syllabus

Introduction
Motivation
Machine Translation
Transformer
TensorFlow
Tensor2Tensor
Training
Open Source
Collaboration
Papers
How does it work
Translation
Speech Recognition
Transformer Models
Image Transformer
MultiGPU
Cloud TPU Pod
Tuning hyper parameters
Mesh tensor flow
Importing data
Problem class
Models
Subclasses
Research subdirectory
Looking Ahead
Mesh
Image Generation
Slice Back
Build Every Tensor
Model Layout
Model Transformer
GitHub

Taught by

TensorFlow

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