GithubHelp home page GithubHelp logo

c1mone / tensorflow-101 Goto Github PK

View Code? Open in Web Editor NEW
184.0 13.0 72.0 7.13 MB

中文的 tensorflow tutorial with jupyter notebooks

License: Other

Jupyter Notebook 100.00% Python 0.01%
tensorflow jupyter-notebook autoencoder deep-learning

tensorflow-101's Introduction

Tensorflow-101

嗨!在這裡我把Tensorflow 官網教學翻譯成中文以及我自己在 ipython 的實作程式碼記錄在 Jupyter Notebook 裡,歡迎大家取用.

  1. Logistic Regression

  2. Softmax Regressions with MNIST

  3. Convolutional Network with MNIST

  4. CNN layer visualization

  5. Save and Restore Model

  6. Autoencoder

  7. Sparse Autoencoder

  8. Convolutional Autoencoder

  9. Denoising Autoencoder

  10. Variational Autoencoder

  11. Reccurent Neural Network with MNIST

  12. Char RNN

  13. word2vec

  14. Generative Adversarial Network with MNIST

  15. DCGAN with MNIST

License

The MIT License (MIT)

Copyright (c) 2016 c1mone

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

tensorflow-101's People

Contributors

c1mone avatar

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

tensorflow-101's Issues

Cannot feed value of shape

您好,我更改placeholder如下:
x = tf.placeholder(tf.float32, shape=[None, 1024])
y_ = tf.placeholder(tf.float32, shape=[None, 5])

於accuracy.eval的 _dict出現錯誤如下:
Cannot feed value of shape (1, 32, 32, 1) for Tensor 'Placeholder:0', which has shape '(?, 1024)'

softmax_cross_entropy_with_logits報錯誤

剛開始學習, 很開心看到有這個資源
但執行到softmax_cross_entropy_with_logits時
報出以下錯誤: ValueError: Only call softmax_cross_entropy_with_logits with named arguments (labels=..., logits=..., ...)
不知道是為什麼呢?

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.