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https://github.com/seopbo/CS20

Refactoring contents and codes of CS20 : Tensorflow for Deep Learning Research
https://github.com/seopbo/CS20

tensorflow

Last synced: 6 days ago
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Refactoring contents and codes of CS20 : Tensorflow for Deep Learning Research

Host: GitHub
URL: https://github.com/seopbo/CS20
Owner: seopbo
License: mit
Created: 2018-04-22T14:09:38.000Z (over 6 years ago)
Default Branch: master
Last Pushed: 2019-01-18T01:22:15.000Z (almost 6 years ago)
Last Synced: 2024-08-03T01:15:26.238Z (3 months ago)
Topics: tensorflow
Language: Jupyter Notebook
Homepage:
Size: 2.36 MB
Stars: 62
Watchers: 7
Forks: 27
Open Issues: 0
Metadata Files:
- Readme: README.md
- License: LICENSE

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README

# CS 20 : Tensorflow for Deep Learning Research
Refactoring code examples of CS 20 : Tensorflow for Deep Learning Research following tensorflow 2.0 (current tf 1.12)

* notice
+ `{filename}_kd.ipynb` is implemented by using `tf.keras` and `tf.data`
+ `{filename}_de.ipynb` is implemented by using `tf.data` and `eager execution`
+ `{filename}_kde.ipynb` is implemented by using `tf.keras`, `tf.data` and `eager execution`

* syllabus : http://web.stanford.edu/class/cs20si/syllabus.html
* github : https://github.com/chiphuyen/stanford-tensorflow-tutorials
- - -

### 01. Overview of Tensorflow
- Lec01 Overview of Tensorflow example code
- [Lec01_Overview of Tensorflow.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec01_Overview%20of%20Tensorflow/Lec01_Overview%20of%20Tensorflow.ipynb)

### 02. Operations
- Lec02 Operations example code
- [Lec02_Operations.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec02_Operations/Lec02_Operations.ipynb)

### 03. Linear and Logistic Regression
- Simple usage of tf.data
- [How to simply use tf.data.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec03_Linear%20and%20Logistic%20Regression/How%20to%20simply%20use%20tf.data.ipynb)

- Lec03 Linear and Logistic Regression example code
- [Lec03_Linear Regression with mse loss.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec03_Linear%20and%20Logistic%20Regression/Lec03_Linear%20Regression%20with%20mse%20loss.ipynb)
- [Lec03_Linear Regression with huber loss by low-level.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec03_Linear%20and%20Logistic%20Regression/Lec03_Linear%20Regression%20with%20huber%20loss%20by%20low-level.ipynb)
- [Lec03_Linear Regression with huber loss by high-level.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec03_Linear%20and%20Logistic%20Regression/Lec03_Linear%20Regression%20with%20huber%20loss%20by%20high-level.ipynb)
- [Lec03_Linear Regression with tf.data.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec03_Linear%20and%20Logistic%20Regression/Lec03_Linear%20Regression%20with%20tf.data.ipynb)
- [Lec03_Linear Regression with tf.data_de.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec03_Linear%20and%20Logistic%20Regression/Lec03_Linear%20Regression%20with%20tf.data_de.ipynb)
- [Lec03_Logistic Regression with ce loss.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec03_Linear%20and%20Logistic%20Regression/Lec03_Logistic%20Regression%20with%20ce%20loss.ipynb)
- [Lec03_Logistic Regression with tf.data.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec03_Linear%20and%20Logistic%20Regression/Lec03_Logistic%20Regression%20with%20tf.data.ipynb)
- [Lec03_Logistic Regression with tf.data_de.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec03_Linear%20and%20Logistic%20Regression/Lec03_Logistic%20Regression%20with%20tf.data_de.ipynb)

### 04. Eager Execution
+ Lec04 Eager execution example code
* [Lec04_Eager execution.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec04_Eager%20execution/Lec04_Eager%20execution.ipynb)
* [Lec04_Automatic differentiation and gradient tape.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec04_Eager%20execution/Lec04_Automatic%20differentiation%20and%20gradient%20tape.ipynb)
* [Lec04_Custom training basics.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec04_Eager%20execution/Lec04_Custom%20training%20basics.ipynb)
* [Lec04_Custom training walkthrough.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec04_Eager%20execution/Lec04_Custom%20training%20walkthrough.ipynb)
* [Lec04_Custom training subclassing.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec04_Eager%20execution/Lec04_Custom%20training%20subclassing.ipynb)
### 05. Variable sharing and managing experiments
- Simple usage of tf.keras
- [How to use keras.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec05_Variable%20sharing%20and%20managing%20experiments/How%20to%20use%20keras.ipynb)

- Lec05 Variable sharing and managing experiments example code
- [Lec05_Variable sharing.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec05_Variable%20sharing%20and%20managing%20experiments/Lec05_Variable%20sharing.ipynb)
- [Lec05_Randomization.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec05_Variable%20sharing%20and%20managing%20experiments/Lec05_Randomization.ipynb)
- [Lec05_Applied example with tf.placeholder.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec05_Variable%20sharing%20and%20managing%20experiments/Lec05_Applied%20example%20with%20tf.placeholder.ipynb)
- [Lec05_Applied example with tf.data.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec05_Variable%20sharing%20and%20managing%20experiments/Lec05_Applied%20example%20with%20tf.data.ipynb)
- [Lec05_Applied example with tf.data_kde.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec05_Variable%20sharing%20and%20managing%20experiments/Lec05_Applied%20example%20with%20tf.data_kde.ipynb)
- [Lec05_Word2vec_simple.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec05_Variable%20sharing%20and%20managing%20experiments/Lec05_Word2vec_simple.ipynb)

### 06. Introduction to ConvNet
### 07. ConvNet in TensorFlow
- Lec07 ConvNet in TensorFlow example code
- [Lec07_ConvNet mnist by low-level.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec07_ConvNet%20in%20Tensorflow/Lec07_ConvNet%20mnist%20by%20low-level.ipynb)
- [Lec07_ConvNet mnist by high-level.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec07_ConvNet%20in%20Tensorflow/Lec07_ConvNet%20mnist%20by%20high-level.ipynb)
- [Lec07_ConvNet mnist by high-level_kd.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec07_ConvNet%20in%20Tensorflow/Lec07_ConvNet%20mnist%20by%20high-level_kd.ipynb)
- [Lec07_ConvNet mnist by high-level_kde.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec07_ConvNet%20in%20Tensorflow/Lec07_ConvNet%20mnist%20by%20high-level_kde.ipynb)
- [Lec07_ConvNet mnist with Weight initialization and Drop out.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec07_ConvNet%20in%20Tensorflow/Lec07_ConvNet%20mnist%20with%20Weight%20initialization%20and%20Drop%20out.ipynb)
- [Lec07_ConvNet mnist with Weight initialization and Drop out_kde.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec07_ConvNet%20in%20Tensorflow/Lec07_ConvNet%20mnist%20with%20Weight%20initialization%20and%20Drop%20out_kde.ipynb)
- [Lec07_ConvNet mnist with Weight initialization and Batch norm.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec07_ConvNet%20in%20Tensorflow/Lec07_ConvNet%20mnist%20with%20Weight%20initialization%20and%20Batch%20norm.ipynb)
- [Lec07_ConvNet mnist with Weight initialization and Batch norm_kde.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec07_ConvNet%20in%20Tensorflow/Lec07_ConvNet%20mnist%20with%20Weight%20initialization%20and%20Batch%20norm_kde.ipynb)

### 08. Style Transfer
### 09. Variational Auto-Encoders
### 10. Generative Adversarial Networks
### 11. Recurrent Neural Networks
- Presentation
- [To quickly implementing RNN.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec11_Recurrent%20Neural%20Networks/To%20quickly%20implementing%20RNN.ipynb)

- Lec11 Recurrent Neural Networks example code
- many to one, word sentiment classification example
- [Lec11_Many to One Classification by RNN.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec11_Recurrent%20Neural%20Networks/Lec11_Many%20to%20One%20Classification%20by%20RNN.ipynb)
- [Lec11_Many to One Classification by RNN_kde.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec11_Recurrent%20Neural%20Networks/Lec11_Many%20to%20One%20Classification%20by%20RNN_kde.ipynb)
- [Lec11_Many to One Classification by LSTM.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec11_Recurrent%20Neural%20Networks/Lec11_Many%20to%20One%20Classification%20by%20LSTM.ipynb)
- [Lec11_Many to One Classification by GRU.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec11_Recurrent%20Neural%20Networks/Lec11_Many%20to%20One%20Classification%20by%20GRU.ipynb)
- [Lec11_Many to One Classification by Bi-directional RNN.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec11_Recurrent%20Neural%20Networks/Lec11_Many%20to%20One%20Classification%20by%20Bi-directional%20RNN.ipynb)
- [Lec11_Many to One Classification by Bi-directional LSTM.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec11_Recurrent%20Neural%20Networks/Lec11_Many%20to%20One%20Classification%20by%20Bi-directional%20LSTM.ipynb)
- [Lec11_Many to One Classification by Bi-directional GRU.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec11_Recurrent%20Neural%20Networks/Lec11_Many%20to%20One%20Classification%20by%20Bi-directional%20GRU.ipynb)
- [Lec11_Many to One Classification by Stacked RNN with Drop out.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec11_Recurrent%20Neural%20Networks/Lec11_Many%20to%20One%20Classification%20by%20Stacked%20RNN%20with%20Drop%20out.ipynb)
- [Lec11_Many to One Classification by Stacked LSTM with Drop out.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec11_Recurrent%20Neural%20Networks/Lec11_Many%20to%20One%20Classification%20by%20Stacked%20LSTM%20with%20Drop%20out.ipynb)
- [Lec11_Many to One Classification by Stacked GRU with Drop out.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec11_Recurrent%20Neural%20Networks/Lec11_Many%20to%20One%20Classification%20by%20Stacked%20GRU%20with%20Drop%20out.ipynb)
- [Lec11_Many to One Classification by Stacked Bi-directional RNN with Drop out.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec11_Recurrent%20Neural%20Networks/Lec11_Many%20to%20One%20Classification%20by%20Stacked%20Bi-directional%20RNN%20with%20Drop%20out.ipynb)
- [Lec11_Many to One Classification by Stacked Bi-directional LSTM with Drop out.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec11_Recurrent%20Neural%20Networks/Lec11_Many%20to%20One%20Classification%20by%20Stacked%20Bi-directional%20LSTM%20with%20Drop%20out.ipynb)
- [Lec11_Many to One Classification by Stacked Bi-directional GRU with Drop out.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec11_Recurrent%20Neural%20Networks/Lec11_Many%20to%20One%20Classification%20by%20Stacked%20Bi-directional%20GRU%20with%20Drop%20out.ipynb)

- many to many, simple pos-tagger example
- [Lec11_Many to Many Classification by RNN.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec11_Recurrent%20Neural%20Networks/Lec11_Many%20to%20Many%20Classification%20by%20RNN.ipynb)
- [Lec11_Many to Many Classification by LSTM.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec11_Recurrent%20Neural%20Networks/Lec11_Many%20to%20Many%20Classification%20by%20LSTM.ipynb)
- [Lec11_Many to Many Classification by GRU.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec11_Recurrent%20Neural%20Networks/Lec11_Many%20to%20Many%20Classification%20by%20GRU.ipynb)
- [Lec11_Many to Many Classification by Bi-directional RNN.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec11_Recurrent%20Neural%20Networks/Lec11_Many%20to%20Many%20Classification%20by%20Bi-directional%20RNN.ipynb)
- [Lec11_Many to Many Classification by Bi-directional LSTM.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec11_Recurrent%20Neural%20Networks/Lec11_Many%20to%20Many%20Classification%20by%20Bi-directional%20LSTM.ipynb)
- [Lec11_Many to Many Classification by Bi-directional GRU.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec11_Recurrent%20Neural%20Networks/Lec11_Many%20to%20Many%20Classification%20by%20Bi-directional%20GRU.ipynb)
- [Lec11_Many to Many Classification by Stacked RNN with Drop out.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec11_Recurrent%20Neural%20Networks/Lec11_Many%20to%20Many%20Classification%20by%20Stacked%20RNN%20with%20Drop%20out.ipynb)
- [Lec11_Many to Many Classification by Stacked LSTM with Drop out.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec11_Recurrent%20Neural%20Networks/Lec11_Many%20to%20Many%20Classification%20by%20Stacked%20LSTM%20with%20Drop%20out.ipynb)
- [Lec11_Many to Many Classification by Stacked GRU with Drop out.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec11_Recurrent%20Neural%20Networks/Lec11_Many%20to%20Many%20Classification%20by%20Stacked%20GRU%20with%20Drop%20out.ipynb)
- [Lec11_Many to Many Classification by Stacked Bi-directional RNN with Drop out.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec11_Recurrent%20Neural%20Networks/Lec11_Many%20to%20Many%20Classification%20by%20Stacked%20Bi-directional%20RNN%20with%20Drop%20out.ipynb)
- [Lec11_Many to Many Classification by Stacked Bi-directional LSTM with Drop out.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec11_Recurrent%20Neural%20Networks/Lec11_Many%20to%20Many%20Classification%20by%20Stacked%20Bi-directional%20LSTM%20with%20Drop%20out.ipynb)
- [Lec11_Many to Many Classification by Stacked Bi-directional GRU with Drop out.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec11_Recurrent%20Neural%20Networks/Lec11_Many%20to%20Many%20Classification%20by%20Stacked%20Bi-directional%20GRU%20with%20Drop%20out.ipynb)

### 12. Seq2Seq with Attention
- Lec12 Seq2Seq with Attention example code

- encoder decoder (many to many), simple neural machine translation example
- [Lec12_Seq2Seq by Encoder RNN and Decoder RNN.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec12_Seq2Seq%20with%20Attention/Lec12_Seq2Seq%20by%20Encoder%20RNN%20and%20Decoder%20RNN.ipynb)
- [Lec12_Seq2Seq by Encoder Bi-directional RNN and Decoder RNN.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec12_Seq2Seq%20with%20Attention/Lec12_Seq2Seq%20by%20Encoder%20Bi-directional%20RNN%20and%20Decoder%20RNN.ipynb)
- [Lec12_Seq2Seq with Attention by Encoder RNN and Decoder RNN.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec12_Seq2Seq%20with%20Attention/Lec12_Seq2Seq%20with%20Attention%20by%20Encoder%20RNN%20and%20Decoder%20RNN.ipynb)
- [Lec12_Seq2Seq with Attention by Encoder Bi-directional RNN and Decoder RNN.ipynb](https://nbviewer.jupyter.org/github/aisolab/CS20/blob/master/Lec12_Seq2Seq%20with%20Attention/Lec12_Seq2Seq%20with%20Attention%20by%20Encoder%20Bi-directional%20RNN%20and%20Decoder%20RNN.ipynb)