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Beginner workshop on PyTorch - ODSC London 2019 - Nov 20th
Jupyter Notebook Python
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PyTorch 101: building a model step-by-step

Learn the basics of building a PyTorch model using a structured, incremental and from first principles approach. Find out why PyTorch is the fastest growing Deep Learning framework and how to make use of its capabilities: autograd, dynamic computation graph, model classes, data loaders and more.

The main goal of this session is to show you how PyTorch works: we will start with a simple and familiar example in Numpy and "torch" it! At the end of it, you should be able to understand PyTorch's key components and how to assemble them together into a working model.

We will use Google Colab and work our way together into building a complete model in PyTorch. You should be comfortable using Jupyter notebooks, Numpy and, preferably, object oriented programming.

Open it in Google Colab PyTorch101_Colab.ipynb.

If you'd rather use a local environment, please follow these steps (assuming you use Anaconda):

  • Install GraphViz:

  • Create a conda environment: conda create -n pytorch101 pip conda python==3.6.8

  • Activate the conda environment: conda activate pytorch101

  • Install PyTorch:

  • Install other packages: conda install scikit-learn==0.21.3 matplotlib==3.1.1 jupyter==1.0.0 ipywidgets==7.5.1 plotly==4.1.1 -c anaconda

  • Install torchviz: pip install torchviz

  • Clone this repo: git clone

  • Start Jupyter: jupyter notebook

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