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Stanford University - Introduction to Artificial Intelligence

Stanford University - Introduction to Artificial Intelligence

Date: 06-11-2016
Category: Tutorials
Stanford University - Introduction to Artificial Intelligence

Stanford University - Introduction to Artificial Intelligence
WEBRip | English | MP4 + PDF Guide | 640 x 360 | AVC ~250 kbps | 30 fps
AAC | 123 Kbps | 44.1 KHz | 2 channels | ~24 hours | 4.42 GB
Genre: eLearning Video / Science, Cybernetics, Probability

Online Introduction to Artificial Intelligence is based on Stanford CS221, Introduction to Artificial Intelligence. This class introduces students to the basics of Artificial Intelligence, which includes machine learning, probabilistic reasoning, robotics, and natural language processing. The objective of this class is to teach you modern AI. You learn about the basic techniques and tricks of the trade, at the same level we teach our Stanford students. We also aspire to excite you about the field of AI. Whether you are a seasoned professional, a college student, or a curious high school student - everyone can participate.
Course Introduction

Introduction to the Course.

Unit 1 Videos, Transcripts, and Quizzes

1 Introduction.
2 Intelligent Agents.
3 Applications of AI.
4 Terminology.
5 Checkers Answer.
6 Poker.
7 Poker Answer.
8 Robotic Car.
9 Robotic Car Answer.
10 AI and Uncertainty.
11 Examples of AI in Practice.
12 Chinese Translation Answer.
13 Chinese Translation 2 Answer.
14 Chinese Translation 3 Answer.
15 Congratulations.

Unit 2 Videos, Transcripts, and Quizzes

1 Introduction.
2 Route Finding Question.
3 Route Finding.
4 Tree Search.
5 Graph Search.
6 Graph Search Answer.
7 Graph Search Answer.
8 Graph Search Answer.
9 More Graph Search.
10 Graph Search Answer.
11 Graph Search Termination.
12 Uniform Cost Search.
13 Uniform Cost Search.
14 Uniform Cost Search.
15 Uniform Cost Search.
16 Uniform Cost Termination.
17 Uniform Cost Termination Answer.
18 Depth First Search.
19 Search Optimality Answer.
20 Storage Requirements, Completeness.
21 Completeness Answer.
22 More on Uniform Cost Search.
23 A Star Search.
23 A Star Search Answer.
24 A Star Second Question.
24 A Star Second Question Answer.
25 A Star Third Question.
25 A Star Third Question Answer.
26 A Star Fourth Question.
26 A Star Fourth Question Answer.
27 A Star Fifth Question.
27 A Star Fifth Question Answer Mandatory.
28 A Optimistic Heuristics.
29 State Spaces.
29 State Spaces Answer.
30 State Space Diagram and More Complexity.
30 State Space Diagram and More Complexity Answer.
31 Sliding Blocks Puzzle.
31 Sliding Blocks Puzzle Answer.
32 Where is the Intelligence.
33 What Can't Search Do.
34 Note on Implementation.

Homework 1 Videos, Transcripts, and Quizzes

1 Introduction.
2 Peg Solitaire.
3 Peg Solitaire Answer.
4 Loaded Coin.
5 Loaded Coin Answer.
6 Path Through Maze.
7 Path Through Maze Answer.
8 Search Tree.
9 Search Tree Answer.
10 Another Search Tree.
11 Another Search Tree Answer.
12 Search Network.
13 Search Network Answer.
14 A-Star Search.
15 A-Star Search Answer.
16 Congratulations!.

Unit 3 Videos, Transcripts, and Quizzes

Introduction.
Probabilities.
Answer.
Question.
Answer.
Question.
Answer.
Question.
Answer.
Question.
Answer.
Summary.
Dependence.
Answer.
What We Learned.
Weather Quiz.
Answer.
Question.
Answer.
Question.
Answer.
Cancer Quiz.
Answer and Cancer Test.
Answer.
Answer.
Question.
Answer.
Bayes Rule.
Bayes Rule Graphically.
Answer.
More Complex Bayes Networks.
Two Test Cancer Example.
Answer.
Question.
Answer.
Conditional Independence.
Answer.
Question.
Answer.
Absolute vs Conditional Independence.
Answer.
Different Type of Bayes Network.
Answer.
Explaining Away.
Answer.
Question.
Answer.
Question.
Answer.
Conclusion.
Blank.
Answer.
Question.
Answer.
Question.
Answer.
Value of the Network.
D-Separation.
Answer.
D-Separation Example.
Answer.
D-Separation General Definition.
Answer.
Congratulations.

Unit 4 Videos, Transcripts, and Quizzes

Probabilistic Inference.
Answer.
Enumeration.
Answer.
Speeding Up Enumeration.
Answer.
Second Question.
Second Answer.
Third Question.
Third Answer.
Fourth Question.
Fourth Answer.
Causal Direction.
Variable Elimination.
Answer.
More Variable Elimination.
Answer.
Even More Variable Elimination.
Answer.
Summary.
Approximate Inference Sampling.
Sampling Example.
Answer.
More Sampling.
Rejection Sampling.
Likelihood Weighting.
Answer.
Likelihood Weighting is Consistent.
Likelihood Weighting Problems.
Gibbs Sampling.
Monty Hall Problem.

Homework 2 Videos, Transcripts, and Quizzes

Congratulations!.
Introduction.
Question 1 Answer.
Question 1.
Question 2 Answer.
Question 2.
Question 3 Answer.
Question 3.
Question 4 Answer.
Question 4.
Question 5 Answer.
Question 5.
Question 6 Answer.
Question 6.

Unit 5 Videos, Transcripts, and Quizzes

Introduction.
What is Machine Learning.
Answer.
Stanley DARPA Grand Challenge.
Taxonomy.
Supervised Learning.
Occams Razor.
SPAM Detection.
Answer.
Question.
Answer.
Maximum Likelihood 1.
Answer.
Relationship to Bayes Networks.
Answer.
Question.
Answer.
Question.
Answer.
Question.
Answer and Laplace Smoothing.
Answer.
Question.
Answer.
Question.
Answer.
Summary Naive Bayes.
Advanced SPAM Filtering.
Digit Recognition.
Overfitting Prevention.
Classification vs Regression.
Answer.
Linear Regression.
Answer.
More Linear Regression.
Quadratic Loss.
Answer.
Problems with Linear Regression.
Answer.
Linear Regression and Complexity Control.
Minimizing Complicated Loss Functions.
Answer.
Question.
Answer.
Question.
Answer.
Gradient Descent Implementation.
Perceptron.
Answer and SVMs.
k Nearest Neighbors.
kNN Definition.
Answer.
k as Smoothing Parameter.
Problems with kNN.
Congratulations.

Unit 6 Videos, Transcripts, and Quizzes

Unsupervised Learning.
Answer.
Question.
Answer.
Terminology.
Google Street View and Clustering.
k-Means Clustering Example.
k-Means Algorithm.
Answer.
Question.
Answer.
Question.
Answer.
Expectation Maximization.
Gaussian Learning.
Maximum Likelihood.
Answer.
Question.
Answer.
Question.
Answer.
Gaussian Summary.
EM as Generalization of k-Means.
EM Algorithm.
Answer.
Question.
Answer.
Question.
Answer.
Choosing k.
Clustering Summary.
Dimensionality Reduction.
Answer.
Question.
Answer.
Linear Dimensionality Reduction.
Face Example.
Scan Example.
Piece-Wise Linear Projection.
Spectral Clustering.
Answer.
Spectral Clustering Algorithm.
Answer.
Question.
Answer.
Supervised vs Unsupervised Learning.

Homework 3 Videos, Transcripts, and Quizzes

Introduction.
Naive Bayes Laplacian Smoothing.
Naive Bayes Laplacian Smoothing.
Maximum Likelihood.
Linear Regression.
Linear Regression.
k Nearest Neighbors.
k Nearest Neighbors.
Perceptron.
Congratulations.

Unit 7 Videos, Transcripts, and Quizzes

Introduction.
Propositional Logic.
Truth Tables.
Answer.
Question.
Answer.
Question.
Answer.
Terminology.
Answer.
Propositional Logic Limitations.
First Order Logic.
Models.
Syntax.
Vacuum World.
Question.
Answer.
Question.
Answer.

Unit 8 Videos, Transcripts, and Quizzes

Introduction.
Problem Solving vs Planning.
Planning vs Execution.
Vacuum Cleaner Example.
Sensorless Vacumm Cleaner Problem-.
Sensorless Vacuum Cleaner Answer.
Partially Observable Vacuum Cleaner Example.
Stocastic Environment Problem.
Stochastic Environment Answer.
Infinite Sequences.
Finding a Successful Plan-.
Finding a Successful Plan Question.
Finding a Successful Plan Answer.
Problem Solving via Mathematical Notation.
Tracking the Predict Update Cycle.
Classical Planning 1.
Classical Planning 2.
Progression Search.
Regression Search.
Regression vs Progression.
Plan Space Search.
Sliding Puzzle Example.
Situation Calculus 1.
Situation Calculus 2.
Situation Calculus 3.

Homework 4 Videos, Transcripts, and Quizzes

Logic.
Logic ANSWER.
More Logic.
More Logic ANSWER.
Vacuum World.
Vacuum World ANSWER.
More Vacuum World.
More Vacuum World ANSWER.
More Vacuum World.
More Vacuum World ANSWER.
More Vacuum World.
More Vacuum World ANSWER.
More Vacuum World.
More Vacuum World ANSWER.
Monkey and Bananas.
Monkey and Bananas ANSWER.
Situation Calculus.
Situation Calculus ANSWER.

Unit 9 Videos, Transcripts, and Quizzes

Introduction.
Planning Under Uncertainty MDP.
Robot Tour Guide Examples.
MDP Grid World.
Problems with Conventional Planning 1.
Branching Factor Question.
Branching Factor Answer.
Problems with Conventional Planning 2.
Policy Question 1.
Policy Answer 1.
Policy Question 2.
Policy Answer 2.
Policy Question 3.
Policy Answer 3 Question 4.
Policy Answer 4.
MDP and Costs.
Value Iteration 1.
Value Iteration 2.
Value Iteration 3.
Deterministic Question 1.
Deterministic Answer 1.
Deterministic Question 2.
Deterministic Answer 2.
Deterministic Question 3.
Deterministic Answer 3.
Stochastic Question 1.
Stochastic Answer 1.
Stochastic Question 2.
Stochastic Answer 2.
Value Iterations and Policy 1.
Value Iterations and Policy 2.
MDP Conclusion.
Partial Observability Introduction.
POMDP vs MDP.
POMDP.

Unit 10 Videos, Transcripts, and Quizzes

Introduction.
Reinforcement Learning with Backgammon and Helicopters.
Helicopter Video.
Forms of Learning.
Forms of Learning Question.
Forms of Learning Answer.
MDP Review.
Solving an MDP.
Agents of Reinforcement Learning.
Passive vs Active Reinforcement Learning.
Passive Temporal Difference Learning.
Passive Agent Results.
Weaknesses in Passive Reinforcement Learning Question.
Weaknesses in Passive Reinforcement Learning Answer.
Active Reinforcement Learning.
Greedy Agent Results.
Balancing Policy.
Errors in Utility Questions.
Errors in Utility Answers.
Exploration Agents.
Exploration Agent Results.
Q Learning 1.
Q Learning 2.
Pacman and Reinforcement Learning.
Pacman and Reinforcement Learning 2.
Reinforcement Learning Conclusion.

Homework 5 Videos, Transcripts, and Quizzes

Q Learning.
Q Learning Answer.
Function Generalization.
Function Generalization answer.
Passive RL Agent.
Passive RL Agent ANSWER.

Unit 11 Videos, Transcripts, and Quizzes

Introduction.
Hidden Markov Models.
Bayes Network of HMMs.
Localization Problem Examples.
Markov Chain Question 1.
Markov Chain Answer 1.
Markov Chain Question 2.
Markov Chain Answer 2.
Stationary Distribution.
Stationary Distribution Question-.
Stationary Distribution Answer.
Finding Transition Probabilities.
Transition Probabilities Question.
Transition Probabilities Answer.
Probabilities using Laplacian Smoothing Question.
Probabilities using Laplacian Smoothing Answer.
HMM Happy Grumpy Problem.
Happy Grumpy Question.
Happy Grumpy Answer.
Wow You Understand.
HMMs and Robot Localization.
HMM Equations.
HMM Localization Example.
Particle Filters.
Localization and Particle Filters.
Particle Filter Algorithm.
Particle Filters Pros and Cons.
Conclusion.

Unit 12 Videos, Transcripts, and Quizzes

Deterministic Question.
Deterministic Answer.
Single Backup Question.
Single Backup Answer.
Convergence Question.
Convergence Answer.
Optimal Policy Question.
Optimal Policy Answer.

Midterm

Midterm.

Unit 13 Videos, Transcripts, and Quizzes

Introduction.
Technologies Question.
Technologies Answer.
Games Question.
Games Answer.
Single Player Game.
Two Player Game.
Two Player Function.
Time Complexity Question.
Time Complexity Answer.
Space Complexity Question.
Space Complexity Answer.
Chess Question.
Chess Answer.
Complexity Reduction Question.
Complexity Reduction Answer.
Review Question.
Review Answer.
Reduce B.
Reduce B Question.
Reduce B Answer.
Reduce M.
Computing State Values.
Complexity Reduction Benefits.
Pacman Question.
Pacman Answer.
Chance.
Chance Question.
Chance Answer.
Terminal State Question.
Game Tree Question 1.
Game Tree Answer 1.
Game Tree Question 2.
Game Tree Answer 2.
Conclusion.

Unit 14 Videos, Transcripts, and Quizzes

Introduction.
Dominant Strategy Question.
Dominant Strategy Answer.
Pareto Optimal Question.
Pareto Optimal Answer.
Equilibrium Question.
Equilibrium Answer.
Game Console Question 1.
Game Console Answer 1.
Game Console Question 2.
Game Console Answer 2.
2 Finger Morra.
Tree Question.
Tree Answer.
Mixed Strategy.
Solving the Game.
Mixed Strategy Issues.
2x2 Game Question 1.
2x2 Game Answer 1.
2x2 Game Question 2.
2x2 Game Answer 2.
Geometric Interpretation.
Poker.
Game Theory Strategies.
Fed vs Politicians Question.
Fed Vs Politicians Answer.
Mechanism Design.
Auction Question.
Auction Answer.

Unit 15 Videos, Transcripts, and Quizzes

Introduction.
Scheduling.
Schedule Question.
Schedule Answer.
Resources Question.
Resources Answer.
Extending Planning.
Hierarchical Planning.
Refinement Planning.
Reachable States.
Reachable States Question.
Reachable States Answer.
Conformant Plan Question.
Conformant Plan Answer.
Sensory Plan Question.
Sensory Plan Answer.

Homework 6 Videos, Transcripts, and Quizzes

Max Likelihood Question.
Max Likelihood Answer.
Stationary Distribution Question.
Stationary Distribution Answer.
HMM Question.
HMM Answer.
Particle Filter Question 1.
Particle Filter Answer 1.
Particle Filter Question 2.
Particle Filter Answer 2.
Particle Filter Question 3.
Particle Filter Answer 3.
Particle Filter Question 4.
Particle Filter Answer 4.
Max Min Question.
Max Min Answer.
Scheduling Question.
Scheduling Answer.
Game Tree Question.
Game Tree Answer.
Strategy Question.
Strategy Answer.

Unit 16 Videos, Transcripts, and Quizzes

Introduction.
Image Formation.
Projection Length Question.
Projection Length Answer.
Focal Length Question.
Focal Length Answer.
Range Question.
Range Answer.
Perspective Projection.
Vanishing Points.
Vanishing Points Question.
Vanishing Points Answer.
Lenses.
Computer Vision.
Invariance Question A.
Invariance Answer A.
Invariance Question B.
Invariance Answer B.
Invariance Question C.
Invariance Answer C.
Invariance Question D.
Invariance Answer D.
Invariance Question E.
Invariance Answer E.
Final Invariance Type.
Importance of Invariance.
Greyscale Images.
Extracting Features.
Extracting Features Question.
Extracting Features Answer.
Linear Filter.
Horizontal Edge Question.
Horizontal Edge Answer.
Vertical Filter Question.
Vertical Filter Answer.
Filter Results.
Gradient Images.
Canny Edge Detector.
Other Masks.
Prewitt Mask Question.
Prewitt Mask Answer.
Gaussian Kernel Question.
Gaussian Kernel Answer.
Reasons for Gaussian Kernels.
Harris Corner Detector.
Modern Feature Detectors.
Conclusion.

Unit 17 Videos, Transcripts, and Quizzes

Introduction.
Depth Question.
Depth Answer.
Stereo.
Stereo Question.
Stereo Answer.
Solving for Depth.
Solve Depth Question.
Solve Depth Answer.
Change in X Question.
Change in X Answer.
Focal Length Question.
Focal Length Answer.
Correspondence Question.
Correspondence Answer.
Determine Correspondence Question.
Determine Correspondence Answer.
SSD Minimization.
Disparity Maps.
Context Question.
Context Answer.
Alignment 1 Question.
Alignment 1 Answer.
Alignment 2 Question.
Alignment 2 Answer.
Dynamic Programming.
Pixel Correspondence Question 1.
Pixel Correspondence Answer 1.
Pixel Correspondence Question 2.
Pixel Correspondence Answer 2.
Finding the Best Alignment.
Correspondence Issues.
Improving Stereo Vision.

Unit 18 Videos, Transcripts, and Quizzes

Structure from Motion Question.
Structure from Motion Answer.
Projection Question.
Projection Answer.
Structure from Motion Models.
SFM Math.
Recovered Unknowns Question.
Recovered Unknowns Answer.
Conclusion.

Homework 7 Videos, Transcripts, and Quizzes

Perspective Projection.
Perspective Projection Answer.
Linear or Not.
Linear or Not Answer.
Gradient Image.
Gradient Image Answer.
Stereo.
Stereo Answer.
Correspondence in Stereo.
Correspondence Answer.
Structure from Motion.
Motion Answer.

Unit 19 Videos, Transcripts, and Quizzes

Autonomous Vehicle Intro 1.
Autonomous Vehicle Intro 2.
Robotics Introduction.
Robotics Question.
Robotics Answer.
Kinematic Question 1.
Kinematic Answer 1.
Kinematic Question 2.
Kinematic Answer 2.
Dynamic Question.
Dynamic Answer.
Helicopter Question 1.
Helicopter Answer 1.
Helicopter Question 2.
Helicopter Answer 2.
Localization.
Monte Carlo Localization.
Localization Question 1.
Localization Answer 1.
Localization Question 2.
Localization Answer 2.

Unit 20 Videos, Transcripts, and Quizzes

Prediction.
Measurement Question.
Measurement Answer.
Resampling Question.
Resampling Answer.
Planning Question.
Planning Answer.
Road Graph.
Cost Question.
Cost Answer.
Dynamic Programming 1.
Dynamic Programming 2.
Robotic Path Planning.
Path Planning Examples.
Conclusion.

Homework 8 Videos, Transcripts, and Quizzes

State Space Question.
State Space Answer.
Dynamic Programming Question 1.
Dynamic Programming Answer 1.
Dynamic Programming Question 2.
Dynamic Programming Answer 2.
Particle Question 1.
Particle Answer 1.
Particle Question 2.
Particle Answer 2.
Stanley Question.
Stanley Answer.
Motion Model Question.
Motion Model Answer.

Unit 21 Videos, Transcripts, and Quizzes

Introduction.
Language Models.
Bag of Words.
Probabilistic Models.
Language and Learning.
Language Models Question.
Language Models Answer.
Unigram Model Samples.
Bigram Model Samples.
Trigram Model Samples.
N Gram Model Samples.
N Gram Model Question.
N Gram Model Answer.
Probability Question.
Probability Answer.
Language Question.
Language Answer.
Letter Bigram Question.
Letter Bigram Answer.
Trigram Model Question.
Trigram Model Answer.
Classification.
Classification Question.
Classification Answer.
Gzip.
Segmentation.
Segmentation Probabilistic Model.
Probabilistic Model Question.
Probabilistic Model Answer.
Best Segmentation 1.
Best Segmentation 2.
Segment Code.
Segment Question 1.
Segment Answer 1.
Segment Question 2.
Segment Answer 2.
Spelling Correction.
Spelling Data.
Correction Example.
Software Engineering.

Optional Homework Videos, Transcripts, and Quizzes

Project Questions.
Project Answer 01.
Project Answer 02.

Unit 22 Videos, Transcripts, and Quizzes

Sentence Structure.
Parses Question.
Parses Answer.
Problems and Solutions Question.
Problems and Solutions Answer.
Writing Grammars.
PCFG.
PCFG Question.
PCFG Answer.
Probability Origins.
Resolving Ambiguity.
LPCFG.
Parsing into a Tree.
Machine Translation.
Translation Example.

Author: Sebastian Thrun & Peter Norvig


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