Vector quantize, outlier detection, regularized regression (l1 Lasso, l2 ridge), model selection using validation, model evaluation using various metrics (ROC, AOC, confusion matrix, precision, recall, F1), principle component analysis, decision forest, logistic regression, neural networks with PyTorch, variational autoencoders, and convolutional neural networks with PyTorch. Professionally used R to clean and transform data and perform regression and ANOVA.

Project list with Code (partial list – currently updating)

Bird Call Audio Classification using a Convolutional Neural Network – Part 1 – Processing Audio; Part 2 – Transfer Learning Resnet 50; Part 3 – Training a custom CNN.