关于 TensorFlow 的一些资料，多学习models 模块_tensorflow modles/offical

1，关于TensorFlow 官方网站

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官方网站：https://www.tensorflow.org/
github 代码 ：https://github.com/tensorflow 上面包括其他的子项目代码。

关于艺术训练学习的子项目：
https://github.com/tensorflow/magenta
google 研究的模型，分为官方的，研究的。
https://github.com/tensorflow/models
其中官方的模型有几个，在research下面有一堆研究的模型。

2，research 模型介绍

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https://github.com/tensorflow/models/tree/master/research
其中每一个模型下面都是一类问题的解决方案和总结。

比如其中一个叫做 im2txt 识别图片中的信息，转换成描述语言。
https://github.com/tensorflow/models/tree/master/research/im2txt

adversarial_crypto: protecting communications with adversarial neural cryptography.
adversarial_text: semi-supervised sequence learning with adversarial training.
attention_ocr: a model for real-world image text extraction.
audioset: Models and supporting code for use with AudioSet.
autoencoder: various autoencoders.
cognitive_mapping_and_planning: implementation of a spatial memory based mapping and planning architecture for visual navigation.
compression: compressing and decompressing images using a pre-trained Residual GRU network.
delf: deep local features for image matching and retrieval.
differential_privacy: privacy-preserving student models from multiple teachers.
domain_adaptation: domain separation networks.
gan: generative adversarial networks.
im2txt: image-to-text neural network for image captioning.
inception: deep convolutional networks for computer vision.
learning_to_remember_rare_events: a large-scale life-long memory module for use in deep learning.
lfads: sequential variational autoencoder for analyzing neuroscience data.
lm_1b: language modeling on the one billion word benchmark.
namignizer: recognize and generate names.
neural_gpu: highly parallel neural computer.
neural_programmer: neural network augmented with logic and mathematic operations.
next_frame_prediction: probabilistic future frame synthesis via cross convolutional networks.
object_detection: localizing and identifying multiple objects in a single image.
pcl_rl: code for several reinforcement learning algorithms, including Path Consistency Learning.
ptn: perspective transformer nets for 3D object reconstruction.
qa_kg: module networks for question answering on knowledge graphs.
real_nvp: density estimation using real-valued non-volume preserving (real NVP) transformations.
rebar: low-variance, unbiased gradient estimates for discrete latent variable models.
resnet: deep and wide residual networks.
skip_thoughts: recurrent neural network sentence-to-vector encoder.
slim: image classification models in TF-Slim.
street: identify the name of a street (in France) from an image using a Deep RNN.
swivel: the Swivel algorithm for generating word embeddings.
syntaxnet: neural models of natural language syntax.
tcn: Self-supervised representation learning from multi-view video.
textsum: sequence-to-sequence with attention model for text summarization.
transformer: spatial transformer network, which allows the spatial manipulation of data within the network.
video_prediction: predicting future video frames with neural advection.

Neural Models of Syntax. 自然语言神经网络：
https://github.com/tensorflow/models/tree/master/research/syntaxnet

3，介绍视频

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goolge 的youku 账号视频：
介绍TensorFlow：介绍session 变量，线性模型等基础概念。
http://v.youku.com/v_show/id_XMjQ3OTYzODkyMA==.html

网易云课堂

无闻制作的视频，从代码方面讲解的，一些编程技巧的。
http://study.163.com/course/courseMain.htm?courseId=1003209007

udacity 课程：
https://cn.udacity.com/course/deep-learning–ud730

4，总结

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好好的学习下发TensorFlow 的模型，里面有非常多的东西。
而且都是可以直接训练了之后应用的模型。
都是google 分享出来了。以后慢慢研究了。

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