awesome-tensorflow-chinese

Implementation of

An implementations of AlexNet3D. Simple AlexNet model but with 3D convolutional layers (conv3d).

TensorFlow implementation of

Implementation of

Tensorflow implementation of

Neural Network to colorize grayscale images

Real-time object detection on Android using the YOLO network, powered by TensorFlow.

Research project to advance the state of the art in machine intelligence for music and art generation

Implementation of 'YOLO : Real-Time Object Detection'

Release of SyntaxNet, "an open-source neural network framework implemented in TensorFlow that provides a foundation for Natural Language Understanding systems.

An introduction to TensorFlow

Understanding the Internals of TensorFlow Learn Estimators

A joke by Joel Grus

Key Features Illustrated

Step-by-step guide with full code examples on GitHub.

Android TensorFlow Machine Learning Example.

Goes over the implementation of TensorFlow

Develop Deep Learning Models on Theano and TensorFlow Using Keras by Jason Brownlee

Get up and running with the latest numerical computing library by Google and dive deeper into your data, by Giancarlo Zaccone

Convert Caffe models to TensorFlow format

Minimal, modular deep learning library for TensorFlow and Theano

Run Keras models (tensorflow backend) in the browser, with GPU support

Simple framework allowing to read-in ROOT NTuples by converting them to a Numpy array and then use them in Google Tensorflow.

Sonnet is DeepMind's library built on top of TensorFlow for building complex neural networks.

A TensorFlow implementation of the models described in

Recurrent Neural Network classification in TensorFlow with LSTM on cellphone sensor data

Tensorflow howtos and best practices. Covers the basics as well as advanced topics.

Build your first TensorFlow Android app

TensorFlow compiled and running properly on the Raspberry Pi

Learn to use a seq2seq model on simple datasets as an introduction to the vast array of possibilities that this architecture offers

The study is performed on several types of deep learning architectures and we evaluate the performance of the above frameworks when employed on a single machine for both (multi-threaded) CPU and GPU (Nvidia Titan X) settings

In this paper, we extend recently proposed Google TensorFlow for execution on large scale clusters using Message Passing Interface (MPI)

This paper describes the models behind

This paper describes the TensorFlow dataflow model in contrast to existing systems and demonstrate the compelling performance

This paper describes the TensorFlow interface and an implementation of that interface that we have built at Google