Coursera - Probabilistic Graphical Models

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Coursera - Probabilistic Graphical Models

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Name:Coursera - Probabilistic Graphical Models

Infohash: E74F08F0FC699E84A9EB046309727D07D80171C5

Total Size: 1.40 GB

Magnet: Magnet Download

Seeds: 11

Leechers: 0

Stream: Watch Full Movies @ LimeMovies

Last Updated: 2026-01-18 10:00:53 (Update Now)

Torrent added: 2016-06-19 02:24:29

Alternatives:Coursera - Probabilistic Graphical Models Torrents

Torrent Files List

Assignments (Size: 1.40 GB) (Files: 547)

Assignments

Assignment 1

Assignment 1.pdf

276.03 KB

AssignmentToIndex.m

0.59 KB

ComputeJointDistribution.m

1.10 KB

ComputeMarginal.m

1.24 KB

ConvertNetwork.m

3.76 KB

Credit_net.net

4.46 KB

FactorMarginalization.m

1.56 KB

FactorProduct.m

2.27 KB

FactorTutorial.m

6.33 KB

GetValueOfAssignment.m

0.79 KB

IndexToAssignment.m

0.58 KB

ObserveEvidence.m

1.90 KB

SetValueOfAssignment.m

1.13 KB

StandardizeFactors.m

0.57 KB

submit.m

22.40 KB

submitWeb.m

0.81 KB

submit_input.mat

3.08 KB

Assignment 2

AssignmentToIndex.m

0.59 KB

GetValueOfAssignment.m

0.79 KB

IndexToAssignment.m

0.58 KB

PA2Appendix.pdf

98.11 KB

PA2Description.pdf

1.28 MB

SetValueOfAssignment.m

1.13 KB

childCopyGivenFreqsFactor.m

0.67 KB

childCopyGivenParentalsFactor.m

2.55 KB

computeSigmoid.m

0.37 KB

constructDecoupledGeneticNetwork.m

3.82 KB

constructGeneticNetwork.m

3.01 KB

constructSigmoidPhenotypeFactor.m

2.68 KB

generateAlleleGenotypeMappers.m

1.98 KB

genotypeGivenAlleleFreqsFactor.m

3.03 KB

genotypeGivenParentsGenotypesFactor.m

3.19 KB

phenotypeGivenCopiesFactor.m

3.22 KB

phenotypeGivenGenotypeFactor.m

2.01 KB

phenotypeGivenGenotypeMendelianFactor.m

2.26 KB

sampleFactorList.mat

0.39 KB

sampleFactorListDecoupled.mat

0.43 KB

sampleGeneticNetworks.m

4.17 KB

sendToSamiam.m

7.31 KB

sendToSamiamGeneCopy.m

10.18 KB

sendToSamiamInfo.m

0.87 KB

sendToSamiamInfoDecoupled.m

1.10 KB

spinalMuscularAtrophyBayesNet.net

4.13 KB

submit.m

26.23 KB

submitWeb.m

0.51 KB

Assignment 3

AssignmentToIndex.m

0.64 KB

BuildOCRNetwork.m

3.28 KB

ChooseTopSimilarityFactors.m

0.81 KB

ComputeAllSimilarityFactors.m

0.66 KB

ComputeEqualPairwiseFactors.m

0.63 KB

ComputeImageFactor.m

0.68 KB

ComputePairwiseFactors.m

0.89 KB

ComputeSimilarityFactor.m

0.93 KB

ComputeSingletonFactors.m

0.82 KB

ComputeTripletFactors.m

1.00 KB

ComputeWordPredictions.m

1.16 KB

GetValueOfAssignment.m

0.82 KB

ImageSimilarity.m

0.69 KB

IndexToAssignment.m

0.57 KB

PA3Data.mat

14.43 KB

PA3Description.pdf

413.28 KB

PA3Models.mat

53.63 KB

PA3SampleCases.mat

74.29 KB

PA3TestCases.mat

5.34 KB

RunInference.m

1.73 KB

ScoreModel.m

1.15 KB

ScorePredictions.m

2.19 KB

SerializeFactorsFg.m

1.21 KB

SetValueOfAssignment.m

0.84 KB

VisualizeWord.m

0.68 KB

inference

doinference-linux

2.19 MB

doinference-mac

816.25 KB

doinference.exe

3.28 MB

inference-src.zip

2.13 MB

submit.m

20.62 KB

submitWeb.m

0.57 KB

Assignment 4

Assignment 4.pdf

421.29 KB

AssignmentToIndex.m

0.61 KB

CliqueTreeCalibrate.m

1.80 KB

ComputeExactMarginalsBP.m

1.00 KB

ComputeInitialPotentials.m

1.58 KB

ComputeJointDistribution.m

1.24 KB

ComputeMarginal.m

1.20 KB

CreateCliqueTree.m

2.19 KB

DecodedMarginalsToChars.m

0.21 KB

EliminateVar.m

1.31 KB

FactorMarginalization.m

1.65 KB

FactorMaxMarginalization.m

1.69 KB

FactorProduct.m

2.30 KB

GetNextCliques.m

1.35 KB

GetValueOfAssignment.m

0.82 KB

IndexToAssignment.m

0.63 KB

MaxDecoding.m

0.81 KB

ObserveEvidence.m

2.14 KB

PA4Sample.mat

215.28 KB

PA4Test.mat

63.03 KB

PruneTree.m

1.75 KB

SetValueOfAssignment.m

1.15 KB

StandardizeFactors.m

0.61 KB

submit.m

28.24 KB

submitWeb.m

0.57 KB

Assignment 5

Assignment 5.pdf

522.47 KB

AssignmentToIndex.m

0.60 KB

BlockLogDistribution.m

2.81 KB

CheckConvergence.m

1.13 KB

ClusterGraphCalibrate.m

3.36 KB

ComputeApproxMarginalsBP.m

2.28 KB

ComputeInitialPotentials.m

2.10 KB

ConstructRandNetwork.m

1.86 KB

ConstructToyNetwork.m

1.81 KB

CreateClusterGraph.m

1.51 KB

EdgeToFactorCorrespondence.m

0.47 KB

ExtractMarginalsFromSamples.m

1.07 KB

FactorMarginalization.m

1.71 KB

FactorProduct.m

2.30 KB

GetNextClusters.m

1.12 KB

GetValueOfAssignment.m

0.82 KB

GibbsTrans.m

0.99 KB

IndexToAssignment.m

0.63 KB

LogProbOfJointAssignment.m

0.33 KB

MCMCInference.m

5.24 KB

MHGibbsTrans.m

0.57 KB

MHSWTrans.m

3.76 KB

MHUniformTrans.m

0.77 KB

NaiveGetNextClusters.m

1.18 KB

ObserveEvidence.m

2.14 KB

SetValueOfAssignment.m

0.84 KB

SmartGetNextClusters.m

1.35 KB

TestToy.m

1.65 KB

VariableToFactorCorrespondence.m

0.25 KB

VisualizeMCMCMarginals.m

2.49 KB

VisualizeToyImageMarginals.m

0.37 KB

exampleIOPA5.mat

43.64 KB

gaimc

scomponents.m

2.43 KB

sparse_to_csr.m

2.25 KB

rand.m

0.43 KB

randi.m

0.81 KB

randsample.m

1.51 KB

smooth.m

0.42 KB

submit.m

36.86 KB

submit_input.mat

7.76 KB

Assignment 6

Assignment 6.pdf

456.29 KB

AssignmentToIndex.m

0.61 KB

CPDFromFactor.m

0.76 KB

CalculateExpectedUtilityFactor.m

0.90 KB

EliminateVar.m

1.41 KB

FactorMarginalization.m

1.71 KB

FactorProduct.m

2.30 KB

FullI.mat

0.84 KB

GetValueOfAssignment.m

0.82 KB

IndexToAssignment.m

0.63 KB

MultipleUtilityI.mat

0.88 KB

NormalizeCPDFactors.m

0.83 KB

NormalizeFactorValues.m

0.23 KB

ObserveEvidence.m

2.27 KB

OptimizeLinearExpectations.m

1.50 KB

OptimizeMEU.m

1.25 KB

OptimizeWithJointUtility.m

1.06 KB

PrintFactor.m

0.51 KB

SetValueOfAssignment.m

1.15 KB

SimpleCalcExpectedUtility.m

1.05 KB

SimpleOptimizeMEU.m

0.82 KB

TestCases.m

4.80 KB

TestI0.mat

0.83 KB

VariableElimination.m

1.35 KB

submit.m

28.32 KB

submitWeb.m

0.57 KB

Assignment 7

AssignmentToIndex.m

0.59 KB

CliqueTreeCalibrate.m

4.93 KB

ComputeConditionedSingletonFeatures.m

0.97 KB

ComputeExactMarginalsBP.m

2.21 KB

ComputeInitialPotentials.m

3.52 KB

ComputeJointDistribution.m

0.88 KB

ComputeMarginal.m

0.95 KB

ComputeUnconditionedPairFeatures.m

0.71 KB

ComputeUnconditionedSingletonFeatures.m

0.60 KB

CreateCliqueTree.m

2.07 KB

EliminateVar.m

1.31 KB

EmptyFactorStruct.m

0.18 KB

EmptyFeatureStruct.m

0.19 KB

FactorMarginalization.m

1.51 KB

FactorMaxMarginalization.m

1.65 KB

FactorProduct.m

2.11 KB

FactorSum.m

2.16 KB

GenerateAllFeatures.m

2.45 KB

GetNextCliques.m

1.70 KB

GetValueOfAssignment.m

0.81 KB

IndexToAssignment.m

0.57 KB

InstanceNegLogLikelihood.m

2.97 KB

LRAccuracy.m

0.64 KB

LRCostSGD.m

1.46 KB

LRPredict.m

0.50 KB

LRSearchLambdaSGD.m

1.08 KB

LRTrainSGD.m

1.32 KB

MaxDecoding.m

0.64 KB

NumParamsForConditionedFeatures.m

0.31 KB

NumParamsForUnconditionedFeatures.m

0.22 KB

ObserveEvidence.m

1.86 KB

PA7Description.pdf

487.12 KB

Part1Lambdas.mat

0.22 KB

Part2FullDataset.mat

7.19 KB

Part2LogZTest.mat

8.52 KB

Part2Sample.mat

84.69 KB

Part2Test.mat

18.19 KB

PruneTree.m

1.82 KB

SetValueOfAssignment.m

0.84 KB

StochasticGradientDescent.m

1.46 KB

Test1X.mat

1.61 KB

Test1Y.mat

0.18 KB

Train1X.mat

3.80 KB

Train1Y.mat

0.23 KB

Train2X.mat

3.82 KB

Train2Y.mat

0.23 KB

Validation1X.mat

3.73 KB

Validation1Y.mat

0.19 KB

Validation2X.mat

3.73 KB

Validation2Y.mat

0.19 KB

ValidationAccuracy.mat

0.25 KB

VisualizeCharacters.m

0.86 KB

sigmoid.m

0.15 KB

submit.m

20.48 KB

submitWeb.m

0.57 KB

Assignment 8

ClassifyDataset.m

0.73 KB

ComputeLogLikelihood.m

1.10 KB

ConvertAtoG.m

0.48 KB

FitGaussianParameters.m

0.28 KB

FitLinearGaussianParameters.m

1.27 KB

GaussianMutualInformation.m

0.43 KB

LearnCPDsGivenGraph.m

0.98 KB

LearnGraphAndCPDs.m

0.95 KB

LearnGraphStructure.m

0.69 KB

MaxSpanningTree.m

2.05 KB

PA8Data.mat

191.39 KB

PA8Description.pdf

378.22 KB

PA8SampleCases.mat

287.71 KB

SampleGaussian.m

0.23 KB

SampleMultinomial.m

0.29 KB

SamplePose.m

3.22 KB

ShowPose.m

1.40 KB

VisualizeDataset.m

0.31 KB

VisualizeModels.m

0.61 KB

func_DrawLine.m

2.96 KB

lognormpdf.m

0.16 KB

submit.m

23.90 KB

submitWeb.m

0.57 KB

submit_input.mat

453.14 KB

Assignment 9

AssignmentToIndex.m

0.59 KB

CliqueTreeCalibrate.m

3.12 KB

ComputeExactMarginalsHMM.m

1.58 KB

CreateCliqueTreeHMM.m

2.37 KB

EM_HMM.m

4.58 KB

EM_cluster.m

3.19 KB

FactorMarginalization.m

0.80 KB

FitG.m

0.34 KB

FitLG.m

1.61 KB

IndexToAssignment.m

0.57 KB

PA9Data.mat

2.58 MB

PA9Description.pdf

987.21 KB

PA9SampleCases.mat

1.02 MB

RecognizeActions.m

1.41 KB

RecognizeUnknownActions.m

0.25 KB

SavePredictions.m

0.56 KB

ShowPose.m

1.38 KB

VisualizeDataset.m

0.24 KB

YourMethod.txt

0.06 KB

func_DrawLine.m

2.96 KB

lognormpdf.m

0.54 KB

logsumexp.m

0.33 KB

submit.m

22.08 KB

submitWeb.m

0.57 KB

submit_input.mat

841.51 KB

Lectures

Week 1 - 01 Introduction and Overview

01_Welcome_05-35.mp4

7.11 MB

01_Welcome_05-35.srt

10.07 KB

01_Welcome_05-35.txt

6.06 KB

02_Overview_and_Motivation_19-17.mp4

22.99 MB

02_Overview_and_Motivation_19-17.srt

24.70 KB

02_Overview_and_Motivation_19-17.txt

16.83 KB

03_Distributions_04-56.mp4

5.79 MB

03_Distributions_04-56.srt

6.88 KB

03_Distributions_04-56.txt

4.73 KB

04_Factors_06-40.mp4

7.36 MB

04_Factors_06-40.srt

8.49 KB

04_Factors_06-40.txt

5.83 KB

Week 1 - 02 Bayesian Network Fundamentals

01_Semantics__Factorization_17-20.mp4

19.55 MB

01_Semantics__Factorization_17-20.srt

21.13 KB

01_Semantics__Factorization_17-20.txt

14.44 KB

02_Reasoning_Patterns_09-59.mp4

10.78 MB

02_Reasoning_Patterns_09-59.srt

11.87 KB

02_Reasoning_Patterns_09-59.txt

8.11 KB

03_Flow_of_Probabilistic_Influence_14-36.mp4

15.46 MB

03_Flow_of_Probabilistic_Influence_14-36.srt

15.46 KB

03_Flow_of_Probabilistic_Influence_14-36.txt

10.60 KB

04_Conditional_Independence_12-38.mp4

15.51 MB

04_Conditional_Independence_12-38.srt

14.98 KB

04_Conditional_Independence_12-38.txt

10.23 KB

05_Independencies_in_Bayesian_Networks_18-18.mp4

21.54 MB

05_Independencies_in_Bayesian_Networks_18-18.srt

22.93 KB

05_Independencies_in_Bayesian_Networks_18-18.txt

15.66 KB

06_Naive_Bayes_09-52.mp4

10.63 MB

06_Naive_Bayes_09-52.srt

11.13 KB

06_Naive_Bayes_09-52.txt

7.64 KB

07_Application_-_Medical_Diagnosis_09-19.mp4

11.51 MB

07_Application_-_Medical_Diagnosis_09-19.srt

12.06 KB

07_Application_-_Medical_Diagnosis_09-19.txt

8.27 KB

08_Knowledge_Engineering_Example_-_SAMIAM_14-14.mp4

12.76 MB

08_Knowledge_Engineering_Example_-_SAMIAM_14-14.srt

23.03 KB

08_Knowledge_Engineering_Example_-_SAMIAM_14-14.txt

12.49 KB

Week 1 - 03 Template Models

01_Overview_of_Template_Models_10-55.mp4

11.57 MB

01_Overview_of_Template_Models_10-55.srt

12.68 KB

01_Overview_of_Template_Models_10-55.txt

8.67 KB

02_Temporal_Models_-_DBNs_23-02.mp4

26.06 MB

02_Temporal_Models_-_DBNs_23-02.srt

26.34 KB

02_Temporal_Models_-_DBNs_23-02.txt

18.02 KB

03_Temporal_Models_-_HMMs_12-01.mp4

13.58 MB

03_Temporal_Models_-_HMMs_12-01.srt

15.11 KB

03_Temporal_Models_-_HMMs_12-01.txt

10.32 KB

04_Plate_Models_20-08.mp4

22.48 MB

04_Plate_Models_20-08.srt

23.48 KB

04_Plate_Models_20-08.txt

16.02 KB

Week 1 - 04 ML-class Octave Tutorial

01_Basic_Operations_13-59.mp4

17.72 MB

01_Basic_Operations_13-59.srt

16.41 KB

01_Basic_Operations_13-59.txt

11.24 KB

02_Moving_Data_Around_16-07.mp4

20.77 MB

02_Moving_Data_Around_16-07.srt

18.57 KB

02_Moving_Data_Around_16-07.txt

12.74 KB

03_Computing_On_Data_13-15.mp4

15.25 MB

03_Computing_On_Data_13-15.srt

15.92 KB

03_Computing_On_Data_13-15.txt

10.94 KB

04_Plotting_Data_09-38.mp4

13.32 MB

04_Plotting_Data_09-38.srt

11.22 KB

04_Plotting_Data_09-38.txt

7.73 KB

05_Control_Statements-_for_while_if_statements_12-55.mp4

16.49 MB

05_Control_Statements-_for_while_if_statements_12-55.srt

15.09 KB

05_Control_Statements-_for_while_if_statements_12-55.txt

10.38 KB

06_Vectorization_13-48.mp4

16.09 MB

06_Vectorization_13-48.srt

16.66 KB

06_Vectorization_13-48.txt

11.43 KB

07_Working_on_and_Submitting_Programming_Exercises_03-33.mp4

5.46 MB

07_Working_on_and_Submitting_Programming_Exercises_03-33.srt

4.52 KB

07_Working_on_and_Submitting_Programming_Exercises_03-33.txt

3.12 KB

Week 2 - 05 Structured CPDs

01_Overview-_Structured_CPDs_08-00.mp4

9.65 MB

01_Overview-_Structured_CPDs_08-00.srt

9.98 KB

01_Overview-_Structured_CPDs_08-00.txt

6.81 KB

02_Tree-Structured_CPDs_14-37.mp4

16.03 MB

02_Tree-Structured_CPDs_14-37.srt

16.81 KB

02_Tree-Structured_CPDs_14-37.txt

11.50 KB

03_Independence_of_Causal_Influence_13-08.mp4

15.85 MB

03_Independence_of_Causal_Influence_13-08.srt

13.90 KB

03_Independence_of_Causal_Influence_13-08.txt

9.51 KB

04_Continuous_Variables_13-25.mp4

15.33 MB

04_Continuous_Variables_13-25.srt

14.55 KB

04_Continuous_Variables_13-25.txt

9.94 KB

Week 2 - 06 Markov Network Fundamentals

01_Pairwise_Markov_Networks_10-59.mp4

12.56 MB

01_Pairwise_Markov_Networks_10-59.srt

13.50 KB

01_Pairwise_Markov_Networks_10-59.txt

9.26 KB

02_General_Gibbs_Distribution_15-52.mp4

18.93 MB

02_General_Gibbs_Distribution_15-52.srt

16.21 KB

02_General_Gibbs_Distribution_15-52.txt

11.04 KB

03_Conditional_Random_Fields_22-22.mp4

25.06 MB

03_Conditional_Random_Fields_22-22.srt

23.39 KB

03_Conditional_Random_Fields_22-22.txt

16.01 KB

04_Independencies_in_Markov_Networks_04-48.mp4

5.83 MB

04_Independencies_in_Markov_Networks_04-48.srt

5.36 KB

04_Independencies_in_Markov_Networks_04-48.txt

3.67 KB

05_I-maps_and_perfect_maps_20-59.mp4

22.39 MB

05_I-maps_and_perfect_maps_20-59.srt

22.32 KB

05_I-maps_and_perfect_maps_20-59.txt

15.19 KB

06_Log-Linear_Models_22-08.mp4

25.76 MB

06_Log-Linear_Models_22-08.srt

26.75 KB

06_Log-Linear_Models_22-08.txt

16.58 KB

07_Shared_Features_in_Log-Linear_Models_08-28.mp4

10.01 MB

07_Shared_Features_in_Log-Linear_Models_08-28.srt

9.03 KB

07_Shared_Features_in_Log-Linear_Models_08-28.txt

6.22 KB

Week 3 - 07 Representation Wrapup-Knowledge Engineering

01_Knowledge_Engineering_23-05.mp4

24.64 MB

01_Knowledge_Engineering_23-05.srt

28.20 KB

01_Knowledge_Engineering_23-05.txt

18.28 KB

Week 3 - 08 Inference-Variable Elimination

01_Overview-_Conditional_Probability_Queries_15-22.mp4

9.01 MB

01_Overview-_Conditional_Probability_Queries_15-22.srt

17.44 KB

01_Overview-_Conditional_Probability_Queries_15-22.txt

11.90 KB

02_Overview-_MAP_Inference_09-42.mp4

5.87 MB

02_Overview-_MAP_Inference_09-42.srt

11.17 KB

02_Overview-_MAP_Inference_09-42.txt

7.67 KB

03_Variable_Elimination_Algorithm_16-17.mp4

11.11 MB

03_Variable_Elimination_Algorithm_16-17.srt

17.51 KB

03_Variable_Elimination_Algorithm_16-17.txt

11.97 KB

04_Complexity_of_Variable_Elimination_12-48.mp4

14.70 MB

04_Complexity_of_Variable_Elimination_12-48.srt

12.85 KB

04_Complexity_of_Variable_Elimination_12-48.txt

8.84 KB

05_Graph-Based_Perspective_on_Variable_Elimination_15-25.mp4

9.55 MB

05_Graph-Based_Perspective_on_Variable_Elimination_15-25.srt

14.82 KB

05_Graph-Based_Perspective_on_Variable_Elimination_15-25.txt

10.14 KB

06_Finding_Elimination_Orderings_11-58.mp4

8.77 MB

06_Finding_Elimination_Orderings_11-58.srt

14.10 KB

06_Finding_Elimination_Orderings_11-58.txt

9.68 KB

Week 3 - 09 Inference-Belief Propagation Part 1

01_Belief_Propagation_21-21.mp4

13.25 MB

01_Belief_Propagation_21-21.srt

23.84 KB

01_Belief_Propagation_21-21.txt

16.30 KB

02_Properties_of_Cluster_Graphs_15-00.mp4

9.73 MB

02_Properties_of_Cluster_Graphs_15-00.srt

16.51 KB

02_Properties_of_Cluster_Graphs_15-00.txt

11.31 KB

Week 4 - 10 Inference-Belief Propagation Part 2

01_Properties_of_Belief_Propagation_9-31.mp4

5.75 MB

01_Properties_of_Belief_Propagation_9-31.srt

10.45 KB

01_Properties_of_Belief_Propagation_9-31.txt

7.17 KB

02_Clique_Tree_Algorithm_-_Correctness_18-23.mp4

10.48 MB

02_Clique_Tree_Algorithm_-_Correctness_18-23.srt

20.09 KB

02_Clique_Tree_Algorithm_-_Correctness_18-23.txt

13.70 KB

03_Clique_Tree_Algorithm_-_Computation_16-18.mp4

8.72 MB

03_Clique_Tree_Algorithm_-_Computation_16-18.srt

16.09 KB

03_Clique_Tree_Algorithm_-_Computation_16-18.txt

11.00 KB

04_Clique_Trees_and_Independence_15-21.mp4

9.52 MB

04_Clique_Trees_and_Independence_15-21.srt

16.93 KB

04_Clique_Trees_and_Independence_15-21.txt

11.58 KB

05_Clique_Trees_and_VE_16-17.mp4

10.55 MB

05_Clique_Trees_and_VE_16-17.srt

17.70 KB

05_Clique_Trees_and_VE_16-17.txt

12.13 KB

06_BP_In_Practice_15-38.mp4

9.20 MB

06_BP_In_Practice_15-38.srt

17.30 KB

06_BP_In_Practice_15-38.txt

11.84 KB

07_Loopy_BP_and_Message_Decoding_21-42.mp4

13.15 MB

07_Loopy_BP_and_Message_Decoding_21-42.srt

26.53 KB

07_Loopy_BP_and_Message_Decoding_21-42.txt

18.14 KB

Week 4 - 11 Inference-MAP Estimation Part 1

01_Max_Sum_Message_Passing_20-27.mp4

12.65 MB

01_Max_Sum_Message_Passing_20-27.srt

22.26 KB

01_Max_Sum_Message_Passing_20-27.txt

15.24 KB

02_Finding_a_MAP_Assignment_3-57.mp4

2.67 MB

02_Finding_a_MAP_Assignment_3-57.srt

5.12 KB

02_Finding_a_MAP_Assignment_3-57.txt

3.50 KB

Week 5 - 12 Inference- MAP Estimation Part 2

01_Tractable_MAP_Problems_15-04.mp4

9.69 MB

01_Tractable_MAP_Problems_15-04.srt

18.93 KB

01_Tractable_MAP_Problems_15-04.txt

12.92 KB

02_Dual_Decomposition_-_Intuition_17-46.mp4

11.20 MB

02_Dual_Decomposition_-_Intuition_17-46.srt

19.57 KB

02_Dual_Decomposition_-_Intuition_17-46.txt

13.45 KB

03_Dual_Decomposition_-_Algorithm_16-16.mp4

9.74 MB

03_Dual_Decomposition_-_Algorithm_16-16.srt

18.45 KB

03_Dual_Decomposition_-_Algorithm_16-16.txt

12.62 KB

Week 5 - 13 Inference- Sampling Methods

01_Simple_Sampling_23-37.mp4

13.78 MB

01_Simple_Sampling_23-37.srt

26.21 KB

01_Simple_Sampling_23-37.txt

17.93 KB

02_Markov_Chain_Monte_Carlo_14-18.mp4

9.21 MB

02_Markov_Chain_Monte_Carlo_14-18.srt

17.00 KB

02_Markov_Chain_Monte_Carlo_14-18.txt

11.62 KB

03_Using_a_Markov_Chain_15-27.mp4

9.53 MB

03_Using_a_Markov_Chain_15-27.srt

17.88 KB

03_Using_a_Markov_Chain_15-27.txt

12.24 KB

04_Gibbs_Sampling_19-26.mp4

12.50 MB

04_Gibbs_Sampling_19-26.srt

19.56 KB

04_Gibbs_Sampling_19-26.txt

13.40 KB

05_Metropolis_Hastings_Algorithm_27-06.mp4

16.91 MB

05_Metropolis_Hastings_Algorithm_27-06.srt

32.46 KB

05_Metropolis_Hastings_Algorithm_27-06.txt

22.17 KB

Week 6 - 14 Inference- Temporal Models and Wrap-up

01_Inference_in_Temporal_Models_19-43.mp4

23.31 MB

01_Inference_in_Temporal_Models_19-43.srt

24.75 KB

01_Inference_in_Temporal_Models_19-43.txt

16.92 KB

02_Inference-_Summary_12-45.mp4

14.16 MB

02_Inference-_Summary_12-45.srt

16.35 KB

02_Inference-_Summary_12-45.txt

11.15 KB

Week 6 - 15 Decision Theory

01_Maximum_Expected_Utility_25-57.mp4

28.99 MB

01_Maximum_Expected_Utility_25-57.srt

29.85 KB

01_Maximum_Expected_Utility_25-57.txt

20.38 KB

02_Utility_Functions_18-15.mp4

19.68 MB

02_Utility_Functions_18-15.srt

21.01 KB

02_Utility_Functions_18-15.txt

14.36 KB

03_Value_of_Perfect_Information_17-14.mp4

19.28 MB

03_Value_of_Perfect_Information_17-14.srt

21.64 KB

03_Value_of_Perfect_Information_17-14.txt

14.96 KB

Week 6 - 16 ML-class Revision

01_Regularization-_The_Problem_of_Overfitting_09-42.mp4

11.15 MB

01_Regularization-_The_Problem_of_Overfitting_09-42.srt

12.91 KB

01_Regularization-_The_Problem_of_Overfitting_09-42.txt

8.79 KB

02_Regularization-_Cost_Function_10-10.mp4

11.63 MB

02_Regularization-_Cost_Function_10-10.srt

12.79 KB

02_Regularization-_Cost_Function_10-10.txt

8.56 KB

03_Evaluating_a_Hypothesis_07-35.mp4

8.48 MB

03_Evaluating_a_Hypothesis_07-35.srt

9.10 KB

03_Evaluating_a_Hypothesis_07-35.txt

6.26 KB

04_Model_Selection_and_Train_Validation_Test_Sets_12-03.mp4

14.07 MB

04_Model_Selection_and_Train_Validation_Test_Sets_12-03.srt

16.03 KB

04_Model_Selection_and_Train_Validation_Test_Sets_12-03.txt

10.98 KB

05_Diagnosing_Bias_vs_Variance_07-42.mp4

8.97 MB

05_Diagnosing_Bias_vs_Variance_07-42.srt

10.44 KB

05_Diagnosing_Bias_vs_Variance_07-42.txt

7.17 KB

06_Regularization_and_Bias_Variance_11-20.mp4

12.60 MB

06_Regularization_and_Bias_Variance_11-20.srt

14.83 KB

06_Regularization_and_Bias_Variance_11-20.txt

10.16 KB

Week 6 - 17 Learning-Overview

01_Learning-_Overview_15-35.mp4

17.51 MB

01_Learning-_Overview_15-35.srt

19.49 KB

01_Learning-_Overview_15-35.txt

13.33 KB

Week 7 - 18 Learning- Parameter Estimation in BNs

01_Maximum_Likelihood_Estimation_14-59.mp4

15.15 MB

01_Maximum_Likelihood_Estimation_14-59.srt

15.40 KB

01_Maximum_Likelihood_Estimation_14-59.txt

10.61 KB

02_Maximum_Likelihood_Estimation_for_Bayesian_Networks_15-49.mp4

17.72 MB

02_Maximum_Likelihood_Estimation_for_Bayesian_Networks_15-49.srt

16.74 KB

02_Maximum_Likelihood_Estimation_for_Bayesian_Networks_15-49.txt

11.43 KB

03_Bayesian_Estimation_15-27.mp4

18.66 MB

03_Bayesian_Estimation_15-27.srt

17.73 KB

03_Bayesian_Estimation_15-27.txt

12.12 KB

04_Bayesian_Prediction_13-40.mp4

16.21 MB

04_Bayesian_Prediction_13-40.srt

15.00 KB

04_Bayesian_Prediction_13-40.txt

10.25 KB

05_Bayesian_Estimation_for_Bayesian_Networks_17-02.mp4

21.16 MB

05_Bayesian_Estimation_for_Bayesian_Networks_17-02.srt

18.90 KB

05_Bayesian_Estimation_for_Bayesian_Networks_17-02.txt

12.96 KB

Week 7 - 19 Learning- Parameter Estimation in MNs

01_Maximum_Likelihood_for_Log-Linear_Models_28-47.mp4

34.60 MB

01_Maximum_Likelihood_for_Log-Linear_Models_28-47.srt

30.93 KB

01_Maximum_Likelihood_for_Log-Linear_Models_28-47.txt

21.13 KB

02_Maximum_Likelihood_for_Conditional_Random_Fields_13-24.mp4

15.10 MB

02_Maximum_Likelihood_for_Conditional_Random_Fields_13-24.srt

15.76 KB

02_Maximum_Likelihood_for_Conditional_Random_Fields_13-24.txt

10.79 KB

03_MAP_Estimation_for_MRFs_and_CRFs_9-59.mp4

11.29 MB

03_MAP_Estimation_for_MRFs_and_CRFs_9-59.srt

12.37 KB

03_MAP_Estimation_for_MRFs_and_CRFs_9-59.txt

8.47 KB

Week 8 - 20 Structure Learning

01_Structure_Learning_Overview_5-49.mp4

6.66 MB

01_Structure_Learning_Overview_5-49.srt

7.82 KB

01_Structure_Learning_Overview_5-49.txt

5.34 KB

02_Likelihood_Scores_16-49.mp4

18.73 MB

02_Likelihood_Scores_16-49.srt

18.84 KB

02_Likelihood_Scores_16-49.txt

12.90 KB

03_BIC_and_Asymptotic_Consistency_11-26.mp4

12.53 MB

03_BIC_and_Asymptotic_Consistency_11-26.srt

13.59 KB

03_BIC_and_Asymptotic_Consistency_11-26.txt

9.32 KB

04_Bayesian_Scores_20-35.mp4

22.62 MB

04_Bayesian_Scores_20-35.srt

23.84 KB

04_Bayesian_Scores_20-35.txt

16.26 KB

05_Learning_Tree_Structured_Networks_12-05.mp4

14.46 MB

05_Learning_Tree_Structured_Networks_12-05.srt

13.93 KB

05_Learning_Tree_Structured_Networks_12-05.txt

9.55 KB

06_Learning_General_Graphs-_Heuristic_Search_23-36.mp4

26.77 MB

06_Learning_General_Graphs-_Heuristic_Search_23-36.srt

30.24 KB

06_Learning_General_Graphs-_Heuristic_Search_23-36.txt

20.67 KB

07_Learning_General_Graphs-_Search_and_Decomposability_15-46.mp4

17.64 MB

Week 9 - 21 Learning With Incomplete Data

01_Learning_With_Incomplete_Data_-_Overview_21-34.mp4

24.86 MB

01_Learning_With_Incomplete_Data_-_Overview_21-34.srt

24.55 KB

01_Learning_With_Incomplete_Data_-_Overview_21-34.txt

16.82 KB

02_Expectation_Maximization_-_Intro_16-17.mp4

18.07 MB

02_Expectation_Maximization_-_Intro_16-17.srt

20.05 KB

02_Expectation_Maximization_-_Intro_16-17.txt

13.74 KB

03_Analysis_of_EM_Algorithm_11-32.mp4

12.88 MB

03_Analysis_of_EM_Algorithm_11-32.srt

13.11 KB

03_Analysis_of_EM_Algorithm_11-32.txt

8.99 KB

04_EM_in_Practice_11-17.mp4

12.69 MB

04_EM_in_Practice_11-17.srt

15.13 KB

04_EM_in_Practice_11-17.txt

10.33 KB

05_Latent_Variables_22-00.mp4

26.70 MB

05_Latent_Variables_22-00.srt

25.27 KB

05_Latent_Variables_22-00.txt

17.29 KB

Week 9 - 22 Learning- Wrapup

01_Summary-_Learning_20-11.mp4

25.69 MB

Week 9 - 23 Summary

01_Class_Summary_24-38.mp4

32.21 MB

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