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Deep Learning GopherNotes

This is a collection of GopherNotes on Deep Learning using Go toolkits

  1. GoTch - Pytorch C++ API Go binding
  2. Tokenizer
  3. Transformer
  4. Gota - Go dataframe
  5. Gonum plot - Plotting and visualizing data

In each folder, there is a Jupyter notebook that can run on local machine using Jupyter + GopherNote kernel or on cloud using Google Colab.

Installation

Run locally

  1. Install Jupyter
  2. Install Jupyter Go kernel - GopherNote
  3. Clone this repo git clone https://github.com/sugarme/nb.git and cd nb
  4. Run Jupyer jupyer lab

Run on Google Colab

  1. Click on one of Google Colab links from Table of Contents to open the notebook
  2. Save the notebook to your Google Drive
  3. Run the first cell as Python runtime
  4. Refresh/reload the browser page/tab. At this point, the notebook will run on Go kernel
  5. Run the other cells.

Table of Contents

  1. Image Open In Colab
  2. MNIST Open In Colab
  3. Tensor Initiation Open In Colab
  4. Tensor Indexing Open In Colab
  5. Tokenizer - BPE model Open In Colab
  6. transformer - BERT Mask Language Model Open In Colab
  7. YOLO v3 model infering Open In Colab

More coming soon...