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Computer Science 171: Introduction to Artificial Intelligence Agents (Presentation Slides) CSP (Presentation Slides) Final + Answers (General Documents) First-Order Logic (Presentation Slides) Games (Presentation Slides) Homework 1 (General Documents) Homework 2 (General Documents) Homework 3 (General Documents) Homework 4 (General Documents) Homework 5 (General Documents) Homework 6 (General Documents) Inference in First-Order Logic (Presentation Slides) Informed Search (Presentation Slides) Intro (Presentation Slides) Learning (Presentation Slides) Logic 1 (Presentation Slides) Logic 2 (Presentation Slides) Midterm+answers (General Documents) Project 1 - Sudoku (General Documents) Project 2 - Datasets (General Documents) Quiz1+answers (General Documents) Quiz2+answers (General Documents) Search (Presentation Slides) testing attributes (General Documents) testing labels (General Documents) training data attributes (General Documents) training data labels (General Documents) Uncertainty (Presentation Slides) Uninformed Search (Presentation Slides) Computer Science 273A: Machine Learning answer sheet HW1 (General Documents) answer sheet HW2 (General Documents) answer sheet HW3 (General Documents) answer sheet HW4 (General Documents) answer sheet HW5 (General Documents) answer sheet HW6 (General Documents) answer sheet HW7 (General Documents) Clustering (ps) (General Documents) Convex Optimization (Lecture Notes) DecisionTrees, Bagging, Boosting (Presentation Slides) Evaluation of Results (Presentation Slides) Fisher LDA (Lecture Notes) Homework 1 (General Documents) Homework 2 (General Documents) Homework 3 (General Documents) Homework 4 (General Documents) Homework 5 (General Documents) Homework 6 (General Documents) Homework 7 (General Documents) Intro, kNN, Logistic Regression, Overfitting (Presentation Slides) Kernel & Spectral Clustering (Lecture Notes) Kernel Canonical Correlation Analysis (Lecture Notes) Kernel PCA (Lecture Notes) Nural Networks (Presentation Slides) Support Vector Machines (Presentation Slides) Unsupervised Learning (Presentation Slides) Computer Science 273B: Kernel-Based Learning Convex Optimization (Lecture Notes) Fisher Linear Discriminant Analysis (Lecture Notes) Kernel Canonical Correlation Analysis (Lecture Notes) Kernel Introduction (Presentation Slides) Kernel PCA (Lecture Notes) Ridge Regression (Lecture Notes) RKHS (Presentation Slides) Support Vector Regression (Lecture Notes) SVMS (Lecture Notes) Inside UCI Lecture Series Research and Statistics: A Personal Account (Video/Audio Lectures)