Machine Learning Algorithms applied to data from recordings of individuals pronouncing each letter of the English alphabet using glmnet, randomForests, xgboost
Core machine learning concepts such as:
- choosing loss functions and evaluation metrics
- splitting the data into training, validation, and testing sets
- cross-validation patterns for tuning hyper-parameters.
Apply ML Algorithms:
- elastic net (a generalization of ridge and lasso regression) [glmnet]
- random forests [randomForests]
- gradient boosting [xgboost]
Data Source: