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fileCoursera-机器学习基石-2013-林轩田-1ivGU

Coursera 机器学习基石 2013 林轩田
  • MP401 The Learning Problem\\/1 - 3 - Applications of chine Learning (18-56).mp422.31MB
  • MP401 The Learning Problem\\/1 - 2 - What is chine Learning (18-28).mp415.94MB
  • MP401 The Learning Problem\\/1 - 1 - Course Introduction (10-58).mp413.79MB
  • MP401 The Learning Problem\\/1 - 5 - chine Learning and Other Fields (10-21).mp411.97MB
  • MP401 The Learning Problem\\/1 - 4 - Components of chine Learning (11-45).mp410.66MB
  • MP402 Learning to Answer Yes or No\\/2 - 4 - Non-Separable Data (12-55).mp433.75MB
  • MP402 Learning to Answer Yes or No\\/2 - 1 - Perceptron Hypothesis Set (15-42).mp418.55MB
  • MP402 Learning to Answer Yes or No\\/2 - 2 - Perceptron Learning Algorithm (PLA) (19-46).mp416.61MB
  • MP402 Learning to Answer Yes or No\\/2 - 3 - Guarantee of PLA (12-37).mp414.45MB
  • MP403 Types of Learning\\/3 - 2 - Learning with Different Data Label (18-12).mp450.14MB
  • MP403 Types of Learning\\/3 - 4 - Learning with Different Input Space (14-13).mp440.89MB
  • MP403 Types of Learning\\/3 - 3 - Learning with Different Protocol (11-09).mp431.41MB
  • MP403 Types of Learning\\/3 - 1 - Learning with Different Output Space (17-26).mp416.16MB
  • MP404 Feasibility of Learning\\/4 - 4 - Connection to Real Learning (18-06).mp415.05MB
  • MP404 Feasibility of Learning\\/4 - 3 - Connection to Learning (16-46).mp414.29MB
  • MP404 Feasibility of Learning\\/4 - 1 - Learning is Impossible- (13-32).mp411.47MB
  • MP404 Feasibility of Learning\\/4 - 2 - Probability to the Rescue (11-33).mp49.86MB
  • MP405 Training versus Testing\\/5 - 3 - Effective Number of Hypotheses (16-17).mp413.12MB
  • MP405 Training versus Testing\\/5 - 2 - Effective Number of Lines (15-26).mp412.57MB
  • MP405 Training versus Testing\\/5 - 1 - Recap and Preview (13-44).mp411.35MB
  • MP405 Training versus Testing\\/5 - 4 - Break Point (07-44).mp46.60MB
  • MP406 Theory of Generalization\\/6 - 4 - A Pictorial Proof (16-01).mp412.85MB
  • MP406 Theory of Generalization\\/6 - 3 - Bounding Function- Inductive Cases (14-47).mp411.64MB
  • MP406 Theory of Generalization\\/6 - 1 - Restriction of Break Point (14-18).mp411.52MB
  • MP406 Theory of Generalization\\/6 - 2 - Bounding Function- Basic Cases (06-56).mp45.50MB
  • MP407 The VC Dimension\\/7 - 4 - Interpreting VC Dimension (17-13).mp413.55MB
  • MP407 The VC Dimension\\/7 - 1 - Definition of VC Dimension (13-10).mp410.67MB
  • MP407 The VC Dimension\\/7 - 2 - VC Dimension of Perceptrons (13-27).mp49.97MB
  • MP407 The VC Dimension\\/7 - 3 - Physical Intuition of VC Dimension (6-11).mp45.16MB
  • MP408 se and Error\\/8 - 1 - Noise and Probabilistic Target (17-01).mp413.93MB
  • MP408 se and Error\\/8 - 4 - Weighted Classification (16-54).mp413.11MB
  • MP408 se and Error\\/8 - 2 - Error Measure (15-10).mp411.40MB
  • MP408 se and Error\\/8 - 3 - Algorithmic Error Measure (13-46).mp410.98MB
  • MP409 Linear Regression\\/9 - 3 - Generalization Issue (20-34).mp415.28MB
  • MP409 Linear Regression\\/9 - 2 - Linear Regression Algorithm (20-03).mp414.51MB
  • MP409 Linear Regression\\/9 - 4 - Linear Regression for Binary Classification (11-23).mp49.05MB
  • MP409 Linear Regression\\/9 - 1 - Linear Regression Problem (10-08).mp48.04MB
  • MP410 Logistic Regression\\/10 - 4 - Gradient Descent (19-18).mp414.91MB
  • MP410 Logistic Regression\\/10 - 3 - Gradient of Logistic Regression Error (15-38).mp412.37MB
  • MP410 Logistic Regression\\/10 - 2 - Logistic Regression Error (15-58).mp411.96MB
  • MP410 Logistic Regression\\/10 - 1 - Logistic Regression Problem (14-33).mp411.94MB
  • MP411 Linear Models for Classification\\/11 - 1 - Linear Models for Binary Classification (21-35).mp416.91MB
  • MP411 Linear Models for Classification\\/11 - 3 - Multiclass via Logistic Regression (14-18).mp411.28MB
  • MP411 Linear Models for Classification\\/11 - 2 - Stochastic Gradient Descent (11-39).mp49.96MB
  • MP411 Linear Models for Classification\\/11 - 4 - Multiclass via Binary Classification (11-35).mp49.36MB
  • MP412 Nonlinear Transfortion\\/12 - 1 - Quadratic Hypothesis (23-47).mp417.92MB
  • MP412 Nonlinear Transfortion\\/12 - 3 - Price of Nonlinear Transform (15-37).mp412.55MB
  • MP412 Nonlinear Transfortion\\/12 - 2 - Nonlinear Transform (09-52).mp48.03MB
  • MP412 Nonlinear Transfortion\\/12 - 4 - Structured Hypothesis Sets (09-36).mp47.31MB
  • MP413 Hazard of Overfitting\\/13 - 3 - Deterministic se (14-07).mp411.92MB
  • MP413 Hazard of Overfitting\\/13 - 2 - The Role of se and Data Size (13-36).mp411.40MB
  • MP413 Hazard of Overfitting\\/13 - 1 - What is Overfitting- (10-45).mp49.01MB
  • MP413 Hazard of Overfitting\\/13 - 4 - Dealing with Overfitting (10-49).mp48.81MB
  • MP414 Regularization\\/14 - 2 - Weight Decay Regularization (24-08).mp418.54MB
  • MP414 Regularization\\/14 - 1 - Regularized Hypothesis Set (19-16).mp415.18MB
  • MP414 Regularization\\/14 - 4 - General Regularizers (13-28).mp411.24MB
  • MP414 Regularization\\/14 - 3 - Regularization and VC Theory (08-15).mp47.14MB
  • MP415 Validation\\/15 - 1 - Model Selection Problem (16-00).mp413.26MB
  • MP415 Validation\\/15 - 3 - Lee-One-Out Cross Validation (16-06).mp412.27MB
  • MP415 Validation\\/15 - 2 - Validation (13-24).mp410.47MB
  • MP415 Validation\\/15 - 4 - V-Fold Cross Validation (10-41).mp49.17MB
  • MP416 Three Learning Principles\\/16 - 3 - Data Snooping (12-28).mp410.80MB
  • MP416 Three Learning Principles\\/16 - 2 - Sampling Bias (11-50).mp410.26MB
  • MP416 Three Learning Principles\\/16 - 1 - Occam-\s Razor (10-08).mp48.21MB
  • MP416 Three Learning Principles\\/16 - 4 - Power of Three (08-49).mp47.55MB
  • PDF投影片\\/lecture_slides-01_handout.pdf6.45MB
  • PDF投影片\\/lecture_slides-16_handout.pdf4.88MB
  • PDF投影片\\/lecture_slides-04_handout.pdf1.80MB
  • PDF投影片\\/lecture_slides-12_handout.pdf1.19MB
  • PDF投影片\\/lecture_slides-15_handout.pdf1.09MB
  • PDF投影片\\/lecture_slides-08_handout.pdf937.54KB
  • PDF投影片\\/lecture_slides-14_handout.pdf878.39KB
  • PDF投影片\\/lecture_slides-13_handout.pdf818.36KB
  • PDF投影片\\/lecture_slides-03_handout.pdf816.43KB
  • PDF投影片\\/lecture_slides-02_handout.pdf800.28KB
  • PDF投影片\\/lecture_slides-09_handout.pdf799.53KB
  • PDF投影片\\/lecture_slides-11_handout.pdf604.81KB
  • PDF投影片\\/lecture_slides-06_handout.pdf557.49KB
  • PDF投影片\\/lecture_slides-10_handout.pdf526.10KB
  • PDF投影片\\/lecture_slides-07_handout.pdf487.03KB
  • PDF投影片\\/lecture_slides-05_handout.pdf446.18KB
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