abstractions-in-python

From Expressions to Machine Learning

Here, we cover the foundations of machine learning, and we learn how to leverage the structure of our expression representation to build our very own machine learning framework, which will be a replica-in-the-small of the PyTorch deep-learning framework. We will then see how to carry out ML training in the (real) PyTorch, and we will discuss convolutional nets, which are very commonly used for image processing and classification tasks.

Notebooks

• From Expressions to Machine Learning Github Colab
• ML with PyTorch Github Colab

Videos

• Building an ML Framework
• Implementing an ML Framework
• ML with PyTorch
• Convolutional Nets

Resources

• PyTorch

There are really too many resources on ML to list them all here. If you are interested in ML, I encourage you to take one of the ML classes offered in the CSE department here at UCSC.