Exploring Harvard University Cs 181 Lecture 22 Machine Learning
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- Intro: Another Example of Bayesian Networks Setting it Up Specific Example of Inference Back to Original Setup: Choosing the ...
- Lecture
- Intro: Mixture Models The Set Up and the Connection to Generative Classification Specific Example: Gaussian Mixture Model ...
- Course Introduction ML Taxonomy Non-Parametric Regression.
- Motivation Probabilistic Classification Overview Discriminative Approach Generative Approach Multi-class Classification.
In-Depth Information on Harvard University Cs 181 Lecture 22 Machine Learning
Lecture 22 Ethical Considerations Support Vector Intro: Probabilistic Embeddings Variations of Probablistic Embeddings Deep Dive into Topic Models Speciifcally Quick Detour: ... Intro: More Neural Network Examples Optimizing the Neural Network Detour: Vector Chain Rule Let's Now Finish The ...
Intro: Real World Example of SVMs Intro to Max Margin (a new objective function) Hard Margin SVM Soft Margin SVM Review of ...
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