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Models built with TensorFlow

License: Apache License 2.0

Python 70.76% Shell 1.43% Jupyter Notebook 1.65% C++ 25.50% Makefile 0.24% Protocol Buffer 0.41%

models's Introduction

TensorFlow Models

This repository contains machine learning models implemented in TensorFlow. The models are maintained by their respective authors.

To propose a model for inclusion please submit a pull request.

Models

  • autoencoder -- various autoencoders
  • inception -- deep convolutional networks for computer vision
  • namignizer -- recognize and generate names
  • neural_gpu -- highly parallel neural computer
  • privacy -- privacy-preserving student models from multiple teachers
  • resnet -- deep and wide residual networks
  • slim -- image classification models in TF-Slim
  • swivel -- the Swivel algorithm for generating word embeddings
  • syntaxnet -- neural models of natural language syntax
  • textsum -- sequence-to-sequence with attention model for text summarization.
  • transformer -- spatial transformer network, which allows the spatial manipulation of data within the network
  • im2txt -- image-to-text neural network for image captioning.
  • [neural_programmer](neural programmer) -- neural network augmented with logic and mathematic operations.

models's People

Contributors

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