In this workshop, students learned about the Convolutional Neural Network (CNN), which is commonly used to find meaning in image data. Data can come in many forms, and likewise, supervised machine learning models have different architectures better suited to making sense of certain types of data. We learned about the basic idea behind CNNs
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The Workshop
We walked through the process of implementing an image classification model in PyTorch, from data preparation to training and testing.
For the workshop example, we made a classifier for the well-known MNIST dataset, a collection of handwritten digits. Convolutional neural networks can perform a wide variety of tasks, and the goal was to allow students to explore different datasets and ask their own questions in part B of this workshop, which was unfortunately cancelled.
We also learned about the Python library PyTorch, a deep learning library that lets you custom-build machine learning models and is also used by professionals and researchers. Many of the upcoming workshops gave students more practice with PyTorch.
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