https://github.com/thomd/deep-learning-notes

Some Notes on Deep Learning
https://github.com/thomd/deep-learning-notes

deep-learning jupyter-notebook machine-learning python pytorch

Last synced: about 1 month ago
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Some Notes on Deep Learning

• Host: GitHub
• URL: https://github.com/thomd/deep-learning-notes
• Owner: thomd
• Created: 2020-03-27T15:46:07.000Z (about 6 years ago)
• Default Branch: master
• Last Pushed: 2021-10-25T21:10:54.000Z (over 4 years ago)
• Last Synced: 2025-02-05T21:43:02.118Z (over 1 year ago)
• Topics: deep-learning, jupyter-notebook, machine-learning, python, pytorch
• Language: Jupyter Notebook
• Homepage:
• Size: 12.5 MB
• Stars: 0
• Watchers: 3
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Deep Learning Notes

Some notes on machine learning from a human learner.

* Notes on Machine Learning [Mathematics](https://nbviewer.jupyter.org/github/thomd/deep-learning-notes/blob/master/ml-math.ipynb)

* Notes on [Tensor Algebra with PyTorch](https://nbviewer.jupyter.org/github/thomd/deep-learning-notes/blob/master/ml-tensoralgebra-pytorch.ipynb)

* Notes on Machine Learning [Data](https://nbviewer.jupyter.org/github/thomd/deep-learning-notes/blob/master/ml-data.ipynb)

* Notes on [Loss Functions](https://nbviewer.jupyter.org/github/thomd/deep-learning-notes/blob/master/ml-loss-functions.ipynb)

* Example of a [CIFAR-10 CNN](https://nbviewer.jupyter.org/github/thomd/deep-learning-notes/blob/master/cnn.ipynb)

* [Image classification with Pre-Trained CNNs](https://nbviewer.jupyter.org/github/thomd/deep-learning-notes/blob/master/cnn-transfer-learning.ipynb)

* On [Style Transfer](https://nbviewer.jupyter.org/github/thomd/deep-learning-notes/blob/master/style-transfer.ipynb)

* Notes on [Recurrent Neural Networks](https://nbviewer.jupyter.org/github/thomd/deep-learning-notes/blob/master/rnn.ipynb) (RNN)

* On [K-Nearest Neighbor (KNN) Classification](https://nbviewer.jupyter.org/github/thomd/deep-learning-notes/blob/master/knn-classifier.ipynb)

## Setup

    conda env create --file environment.yaml

    conda activate ml

    jupyter lab