Exploring Lecture 7 23 Sep Cpsc 340 2020w Machine Learning And Data Mining
Let's dive into the details surrounding Lecture 7 23 Sep Cpsc 340 2020w Machine Learning And Data Mining.
- More Linear Classifiers, Support Vector
- Non-parametric models: K-nearest neighbors, Decision Theory for Darts, Norms https://www.cs.ubc.ca/~fwood/CS340/
- Exploratory
- Feature Engineering, Gmail Priority Inbox.
- Clustering, K-means clustering (demo), K-Means++ https://www.cs.ubc.ca/~fwood/CS340/
In-Depth Information on Lecture 7 23 Sep Cpsc 340 2020w Machine Learning And Data Mining
Ensemble Methods, Random Forests, Empirical Study, Kinect https://www.cs.ubc.ca/~fwood/CS340/ Gradient Descent, Convex Functions https://www.cs.ubc.ca/~fwood/CS340/ Deep Learning Stochastic Gradient.
Kernel Trick.
That wraps up our extensive overview of Lecture 7 23 Sep Cpsc 340 2020w Machine Learning And Data Mining.