Introduction to Lecture 17 19 Oct Cpsc 340 2020w Machine Learning And Data Mining
Let's dive into the details surrounding Lecture 17 19 Oct Cpsc 340 2020w Machine Learning And Data Mining. More Regularization, RBF video, RBF and Regularization video.
Lecture 17 19 Oct Cpsc 340 2020w Machine Learning And Data Mining Comprehensive Overview
More Linear Classifiers, Support Vector Linear Classifiers, Perceptron. Regularization.
Gradient Descent, Convex Functions https://www.cs.ubc.ca/~fwood/CS340/
Summary & Highlights for Lecture 17 19 Oct Cpsc 340 2020w Machine Learning And Data Mining
- Multi-Dimensional Scaling, Nonlinear Dimensionality Reduction, t-SNE demo.
- Boosting, AdaBoost, XGBoost.
- Probabilistic Classifiers: Conditional probability, Naive Bayes, Probabilities and Battleship https://www.cs.ubc.ca/~fwood/CS340/
- Feature Engineering, Gmail Priority Inbox.
- More clustering, DBSCAN (video, demo), Hierarchical Clustering, Phylogenetic Trees https://www.cs.ubc.ca/~fwood/CS340/
That wraps up our extensive overview of Lecture 17 19 Oct Cpsc 340 2020w Machine Learning And Data Mining.