Building further on the concepts covered in the Introduction, Intermediate, and Data Science Python courses, we will introduce Python as a tool for training and testing machine learning (ML) models with a particular focus on deep learning approaches. Specific topics will include an introduction to the PyTorch software library and a brief survey of some of the basic model architectures which it implements. Some prior familiarity with the basic ideas of ML (underfitting vs. overfitting, use of training and test data sets, model performance metrics such as AUC, etc.) and/or linear algebra will be helpful for getting the most out of this course.
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$50