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PyTorch Workshop, Jul 27 2019

Livestream & Recordings

The event was livestreamed on YouTube. Recording can be found here: https://youtu.be/ktGi4f8YU50

Also check out this playlist for shorter videos with better audio:
https://www.youtube.com/watch?v=0OrsXEctt70&list=PLUu6crCNTDeRRljzuCVpwuhHr-zc5t6Et

Setup Instructions

  1. Join the Data Science Network Slack group at dsnet.org and enter the #pytorch-workshop channel.

  2. Download & install Anaconda, and ensure that you can run the conda command (it should be added to your PATH). Please do it before the workshop starts, as it's large download.

  3. Sign up on Jovian and install the jovian Python library, the platform we'll use for sharing and reproducing Jupyter notebooks & Python environments. You can try replicating this notebook to test your installation.

If you are unable to complete Step 2, you can also also run the Jupyter notebooks online using BinderHub, Kaggle Kernels or Google Colab. Just open one of the notebooks below, and use the 'Run' button/dropdown.

Jupyter Notebooks

We'll be using the following Jupyter notebooks during the workshop.

  1. Machine Learning Intro: https://jvn.io/aakashns/8bb4e6a8623d48b1bdedcf6ee4eeab57
  2. PyTorch Basics: https://jvn.io/aakashns/e5cfe043873f4f3c9287507016747ae5
  3. Linear Regression: https://jvn.io/aakashns/e556978bda9343f3b30b3a9fd2a25012
  4. Logistic Regression: https://jvn.io/aakashns/a1b40b04f5174a18bd05b17e3dffb0f0

You can close/run these notebooks using Jovian, to follow along during the workshop.

Kaggle competition for practice: https://www.kaggle.com/c/boston-housing

In [1]:
!pip install jovian --upgrade -q
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import jovian
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jovian.commit(notebook_id='0c205fae9ddd4b9692b8f67abb69bd24')
[jovian] Saving notebook..
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