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c++/pytorch_dcgan_tutorial
c++/pytorch_dcgan_tutorial
 
 
data
data
 
 
.gitignore
.gitignore
 
 
CNN2RNN.ipynb
CNN2RNN.ipynb
 
 
G729VAD.ipynb
G729VAD.ipynb
 
 
GRUAutoencoder.ipynb
GRUAutoencoder.ipynb
 
 
LICENSE
LICENSE
 
 
README.md
README.md
 
 
Youtube-GraphTheory-EdgeWeightedEx.sagews
Youtube-GraphTheory-EdgeWeightedEx.sagews
 
 
allstate_pca.ipynb
allstate_pca.ipynb
 
 
audio_rnn_basic.ipynb
audio_rnn_basic.ipynb
 
 
char-rnn.ipynb
char-rnn.ipynb
 
 
convolution1d_tests.ipynb
convolution1d_tests.ipynb
 
 
coursera-algos-knapsack-ps.ipynb
coursera-algos-knapsack-ps.ipynb
 
 
coursera-algos-twosum.ipynb
coursera-algos-twosum.ipynb
 
 
databricks_python_graphframes_GraphExample.ipynb
databricks_python_graphframes_GraphExample.ipynb
 
 
databricks_python_numpy_spark_kMeansExample.ipynb
databricks_python_numpy_spark_kMeansExample.ipynb
 
 
denoising_autoencoder.ipynb
denoising_autoencoder.ipynb
 
 
imdb_tokenize.ipynb
imdb_tokenize.ipynb
 
 
logistic-regression-pure-julia.ipynb
logistic-regression-pure-julia.ipynb
 
 
macro-hw3-2.ipynb
macro-hw3-2.ipynb
 
 
pymc-test.ipynb
pymc-test.ipynb
 
 
pytorch_attention_audio.py
pytorch_attention_audio.py
 
 
pytorch_basics.ipynb
pytorch_basics.ipynb
 
 
pytorch_embedding_test.ipynb
pytorch_embedding_test.ipynb
 
 
pytorch_tutorial_classify_names.ipynb
pytorch_tutorial_classify_names.ipynb
 
 
rnn_autoencoder.ipynb
rnn_autoencoder.ipynb
 
 
tedlium_labels.ipynb
tedlium_labels.ipynb
 
 
test_VarLenDataset.ipynb
test_VarLenDataset.ipynb
 
 
test_pdb_debugger.ipynb
test_pdb_debugger.ipynb
 
 
test_tqdm.ipynb
test_tqdm.ipynb
 
 
timeseries.ipynb
timeseries.ipynb
 
 

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Programming Notebooks

Python

In the summer of 2016, I spent some time with various free online resources to learn graph theory and basic algorithm programming. Most of these notebooks were written for various assignments in these courses. Not all of my notebooks are here.

List of Courses

  1. Sarada Herke's Graph Theory
  2. Coursera - Social and Economic Networks: Models and Analysis
  3. Coursera - Algorithms: Design and Analysis, Part 1
  4. Coursera - Algorithms: Design and Analysis, Part 2
  5. Coursera - Probabilistic Graphical Models 1: Representation

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A collection of programming notebooks that I've created.

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