Introduction to Aa 19 20 Lecture 1
Exploring Aa 19 20 Lecture 1 reveals several interesting facts. Introduction.
Aa 19 20 Lecture 1 Comprehensive Overview
Supervised learning, minimization (least squares), polynomial regression. PROFESSIONAL PRACTICE II / ARCHITECTURE 544 Fuzzy sets and clustering. Fuzzy c-means. Manifold learning. Second assignment.
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Summary & Highlights for Aa 19 20 Lecture 1
- Classification. Linear separability and discriminants. Logistic Regression. Using linear classifiers in higher dimensions.
- Hierarchical Clustering. Agglomerative and Divisive Clustering.
- Introduction to deep learning.
- Maximum Margin Classifiers. Support vector machines for linear classification.
- Scoring classifiers. Cross-validation. Overfitting, model selection and regularization with logistic regression.
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