Neural Network Tutorial

A tutorial introduction to neural networks, with an eye towards linguistic applications. The repository contains slides as well as a Jupyter Notebook with a hands-on demonstration of basic techniques in building and training a neural network for a semantic task.

Setting up your environment

I recommend using conda from the Anaconda Distribution: https://www.anaconda.com/. My instructions are for UNIX systems (OS X and Linux), but Anaconda should make it easy to follow these steps on Windows as well.

Once installed, you can execute the following:

1. conda create -n nn-tutorial python=3.7
2. conda activate nn-tutorial
3. conda install pytorch torchvision jupyter pandas -c pytorch
4. conda install plotnine -c conda-forge

Note: if you end up having trouble with the Jupyter notebook not being able to find the packages you've installed in your environment, it isn't using the right kernel, and the following may solve this problem (in any case it won't hurt):

5. conda install nb_conda_kernels

Running the tutorial

It can be helpful to conda deactivate from the nn-tutorial environment first. Then:

1. cd DIR, where DIR is a directory of your choice
2. git clone https://github.com/shanest/nn-tutorial.git
3. Alternatively: download the zip file from GitHub and extract it to your directory.
4. conda activate nn-tutorial
5. jupyter notebook

You should now be able to click to open the file tutorial.ipynb, and interact with it!