Media Summary: Nearest neighbors, nearest centroids, cross-validation and grid-search Materials on the course website: ... Text data, bag of words, n-grams, tfidf, stop words, text classification. More information on the class website: ... Feature importance measures, partial dependence plots. Univariate and multivariate feature selection, recursive feature selection.
Applied Machine Learning 2019 Lecture - Detailed Analysis & Overview
Nearest neighbors, nearest centroids, cross-validation and grid-search Materials on the course website: ... Text data, bag of words, n-grams, tfidf, stop words, text classification. More information on the class website: ... Feature importance measures, partial dependence plots. Univariate and multivariate feature selection, recursive feature selection. Course details, timeline, and basic process breakdown. Course link: A quick recap and Q & A on some of the main points of the second half of the course. Grid Search, Randomized Search Bayesian Optimization, SMBO Successive halving, hyperband auto-sklearn Freely borrowed ...
Introduction to neural networks Autograd GPU acceleration Deep Time series formats and tasks Stationarity Seasonal Models Autoregressive models More materials and slides on the course ... Residual Networks, DenseNet, Recurrent Neural Networks. Slides and materials on the course website: ... Decision trees for classification and regression, tree pre-pruning, bagging and ensembles, random forests, extremely randomized ...
