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Lecture 25 Advanced Applications Computer Vision and Robotics

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Lecture 24 NLP and Robotic Cars

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Lecture 23 Kernels and Clustering

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Lecture 22 Perceptron Part 2

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Lecture 21 Perceptron

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Lecture20 Machine Learning Naive Bayes

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Lecture 19 Particle Filters, Dynamic Bayes' Nets, Speech Recognition

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Lecture 18 HMMs

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Lecture 17 Decision Diagrams and VPI

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Lecture 16 BN IV Sampling (some sound issues)

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Lecture 15 -- BN III Variable Elimination

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D-Separation

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Lecture 14 Bayes Nets II Conditional Independence

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Lecture 13 Bayes' Nets 1

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Lecture12 Probability

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Lecture 11 Reinforcement Learning II

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Lecture 10 Reinforcement Learning

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Lecture 9 Markov Decision Process II

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Lecture 8 Markov Decision Processes (MDPs)

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Lecture7 Expectimax and Utilities

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Step by Step Alpha Beta Pruning

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Lecture 6 Zero-Sum Games

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Lecture 4 CSPs

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Lecture 3 Informed Search (A)

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Step-by-Step A Star Search

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Step-by-Step Depth First Tree Search and Breadth First Tree Search

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Lecture 2 Uninformed Search

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Lecture 1 Introduction

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