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.

  • Stochastic Gradient.
  • Exploratory
  • Principal Component Analysis,
  • MLE and MAP, Maximum Likelihood Estimation.
  • 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/ Boosting, AdaBoost, XGBoost. More Regularization, RBF video, RBF and Regularization video. More Linear Classifiers, Support Vector

Gradient Descent, Convex Functions https://www.cs.ubc.ca/~fwood/CS340/

That wraps up our extensive overview of Lecture 7 23 Sep Cpsc 340 2020w Machine Learning And Data Mining.

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