Machine Learning Pedro Domingos torrent, magnet, bt

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Machine Learning Pedro Domingos

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0DB676A6AAFF8C33F9749D5F9C0FA22BF336BC76

Number of Files:

113

Content Size:

8.44GB

Convert On:

2019-07-10

Keywords:

Machine Learning Pedro Domingos

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//btsow.motorcycles/magnet/detail/hash/0DB676A6AAFF8C33F9749D5F9C0FA22BF336BC76

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File Name

Size

01 Introduction & Inductive learning/10. A Framework for Studying Inductive Learning.mp4

201.81MB

01 Introduction & Inductive learning/2. What Is Machine Learning.mp4

47.34MB

01 Introduction & Inductive learning/3. Applications of Machine Learning.mp4

72.6MB

01 Introduction & Inductive learning/4. Key Elements of Machine Learning.mp4

138.36MB

01 Introduction & Inductive learning/5. Types of Learning.mp4

69.72MB

01 Introduction & Inductive learning/6. Machine Learning In Practice.mp4

87.65MB

01 Introduction & Inductive learning/7. What Is Inductive Learning.mp4

28.07MB

01 Introduction & Inductive learning/8. When Should You Use Inductive Learning.mp4

59.29MB

01 Introduction & Inductive learning/9. The Essence of Inductive Learning.mp4

182.51MB

01 Introduction & Inductive learning/1. Class Information.mp4

27.87MB

02 Decision Trees/1. Decision Trees.mp4

40.09MB

02 Decision Trees/2. What Can a Decision Tree Represent.mp4

26.71MB

02 Decision Trees/3. Growing a Decision Tree.mp4

27.79MB

02 Decision Trees/4. Accuracy and Information Gain.mp4

139.93MB

02 Decision Trees/5. Learning with Non Boolean Features.mp4

40.83MB

02 Decision Trees/6. The Parity Problem.mp4

31.96MB

02 Decision Trees/7. Learning with Many Valued Attributes.mp4

39.4MB

02 Decision Trees/8. Learning with Missing Values.mp4

71.97MB

02 Decision Trees/9. The Overfitting Problem.mp4

49.15MB

02 Decision Trees/10. Decision Tree Pruning.mp4

132.24MB

02 Decision Trees/11. Post Pruning Trees to Rules.mp4

149.22MB

02 Decision Trees/12. Scaling Up Decision Tree Learning.mp4

48.81MB

03 Rule Induction/1. Rules vs. Decision Trees.mp4

114.98MB

03 Rule Induction/2. Learning a Set of Rules.mp4

94.67MB

03 Rule Induction/3. Estimating Probabilities from Small Samples.mp4

75.97MB

03 Rule Induction/4. Learning Rules for Multiple Classes.mp4

42.73MB

03 Rule Induction/5. First Order Rules.mp4

76.76MB

03 Rule Induction/6. Learning First Order Rules Using FOIL.mp4

186.93MB

03 Rule Induction/7. Induction as Inverted Deduction.mp4

132.9MB

03 Rule Induction/8. Inverting Propositional Resolution.mp4

68.84MB

03 Rule Induction/9. Inverting First Order Resolution.mp4

149.08MB

04 Instance-Based Learning/1. The K-Nearest Neighbor Algorithm.mp4

151.1MB

04 Instance-Based Learning/2. Theoretical Guarantees on k-NN.mp4

98.11MB

04 Instance-Based Learning/4. The Curse of Dimensionality.mp4

128.31MB

04 Instance-Based Learning/5. Feature Selection and Weighting.mp4

96.68MB

04 Instance-Based Learning/6. Reducing the Computational Cost of k-NN.mp4

94.67MB

04 Instance-Based Learning/7. Avoiding Overfitting in k-NN.mp4

52.61MB

04 Instance-Based Learning/8. Locally Weighted Regression.mp4

38.54MB

04 Instance-Based Learning/9. Radial Basis Function Networks.mp4

31.65MB

04 Instance-Based Learning/10 Case-Based Reasoning.mp4

37.04MB

04 Instance-Based Learning/11. Lazy vs. Eager Learning.mp4

26.37MB

04 Instance-Based Learning/12. Collaborative Filtering.mp4

148.81MB

05 Bayesian Learning/1. Bayesian Methods.mp4

22.13MB

05 Bayesian Learning/2. Bayes' Theorem and MAP Hypotheses.mp4

193.26MB

05 Bayesian Learning/3. Basic Probability Formulas.mp4

46.79MB

05 Bayesian Learning/4. MAP Learning.mp4

101.36MB

05 Bayesian Learning/5. Learning a Real-Valued Function.mp4

78.49MB

05 Bayesian Learning/6. Bayes Optimal Classifier and Gibbs Classifier.mp4

77.89MB

05 Bayesian Learning/7. The Naive Bayes Classifier.mp4

187.05MB

05 Bayesian Learning/8. Text Classification.mp4

88.41MB

05 Bayesian Learning/9. Bayesian Networks.mp4

169.65MB

05 Bayesian Learning/10. Inference in Bayesian Networks.mp4

32.3MB

06 Neural Networks/1. Bayesian Network Review.mp4

18.45MB

06 Neural Networks/2. Learning Bayesian Networks.mp4

31.16MB

06 Neural Networks/3. The EM Algorithm.mp4

62.22MB

06 Neural Networks/4. Example of EM.mp4

64.65MB

06 Neural Networks/5. Learning Bayesian Network Structure.mp4

140.09MB

06 Neural Networks/6. The Structural EM Algorithm.mp4

19.88MB

06 Neural Networks/7. Reverse Engineering the Brain.mp4

59MB

06 Neural Networks/8. Neural Network Driving a Car.mp4

108.47MB

06 Neural Networks/9. How Neurons Work.mp4

62.95MB

06 Neural Networks/10. The Perceptron.mp4

93.5MB

06 Neural Networks/11. Perceptron Training.mp4

79.83MB

06 Neural Networks/12. Gradient Descent.mp4

42.02MB

07 Model Ensembles/1. Gradient Descent Continued.mp4

44.04MB

07 Model Ensembles/2. Gradient Descent vs Perceptron Training.mp4

53.96MB

07 Model Ensembles/3. Stochastic Gradient Descent.mp4

32.22MB

07 Model Ensembles/4. Multilayer Perceptrons.mp4

72.33MB

07 Model Ensembles/5. Backpropagation.mp4

95.82MB

07 Model Ensembles/6. Issues in Backpropagation.mp4

120.86MB

07 Model Ensembles/7. Learning Hidden Layer Representations.mp4

67.97MB

07 Model Ensembles/8. Expressiveness of Neural Networks.mp4

36.22MB

07 Model Ensembles/9. Avoiding Overfitting in Neural Networks.mp4

48.94MB

07 Model Ensembles/10. Model Ensembles.mp4

14.75MB

07 Model Ensembles/11. Bagging.mp4

43.39MB

07 Model Ensembles/12. Boosting- The Basics.mp4

38.93MB

08 Learning Theory/1. Boosting- The Details.mp4

59.03MB

08 Learning Theory/2. Error Correcting Output Coding.mp4

84.78MB

08 Learning Theory/3. Stacking.mp4

83.95MB

08 Learning Theory/4. Learning Theory.mp4

13.68MB

08 Learning Theory/5. 'No Free Lunch' Theorems.mp4

85.54MB

08 Learning Theory/6. Practical Consequences of 'No Free Lunch'.mp4

46.05MB

08 Learning Theory/7. Bias and Variance.mp4

88.09MB

08 Learning Theory/8. Bias Variance Decomposition for Squared Loss.mp4

30.26MB

08 Learning Theory/9. General Bias Variance Decomposition.mp4

84.14MB

08 Learning Theory/10. Bias-Variance Decomposition for Zer -One Loss.mp4

30.88MB

08 Learning Theory/11. Bias and Variance for Other Loss Functions.mp4

31.01MB

08 Learning Theory/12. PAC Learning.mp4

47.87MB

08 Learning Theory/13. How Many Examples Are Enough.mp4

108.75MB

08 Learning Theory/14. Examples and Definition of PAC Learning.mp4

37.93MB

09 Support Vector Machine/1. Agnostic Learning.mp4

97.96MB

09 Support Vector Machine/2. VC Dimension.mp4

72.96MB

09 Support Vector Machine/3. VC Dimension of Hyperplanes.mp4

75.24MB

09 Support Vector Machine/4. Sample Complexity from VC Dimension.mp4

9.29MB

09 Support Vector Machine/5. Support Vector Machines.mp4

55.28MB

09 Support Vector Machine/6. Perceptrons as Instance-Based Learning.mp4

98.82MB

09 Support Vector Machine/7. Kernels.mp4

123.96MB

09 Support Vector Machine/8. Learning SVMs.mp4

117.58MB

09 Support Vector Machine/9. Constrained Optimization.mp4

140.76MB

09 Support Vector Machine/10. Optimization with Inequality Constraints.mp4

113.9MB

09 Support Vector Machine/11. The SMO Algorithm.mp4

47.88MB

10 Clustering and Dimensionality Reduction/1. Handling Noisy Data in SVMs.mp4

62.58MB

10 Clustering and Dimensionality Reduction/2. Generalization Bounds for SVMs.mp4

71.01MB

10 Clustering and Dimensionality Reduction/3. Clustering and Dimensionality Reduction.mp4

61.91MB

10 Clustering and Dimensionality Reduction/4. K-Means Clustering.mp4

53.29MB

10 Clustering and Dimensionality Reduction/5. Mixture Models.mp4

111.61MB

10 Clustering and Dimensionality Reduction/6. Mixtures of Gaussians.mp4

41.64MB

10 Clustering and Dimensionality Reduction/7. EM Algorithm for Mixtures of Gaussians.mp4

96.14MB

10 Clustering and Dimensionality Reduction/8. Mixture Models vs K-Means vs. Bayesian Networks.mp4

57.56MB

10 Clustering and Dimensionality Reduction/9. Hierarchical Clustering.mp4

36.59MB

10 Clustering and Dimensionality Reduction/10. Principal Components Analysis.mp4

107.06MB

10 Clustering and Dimensionality Reduction/11. Multidimensional Scaling.mp4

55.93MB

10 Clustering and Dimensionality Reduction/12. Nonlinear Dimensionality Reduction.mp4

96.75MB

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