Andrew Ng Assistant Professor, Department of Computer Science Stanford

Andrew Ng

Assistant Professor, Department of Computer Science
Stanford

Courses

  1. Machine Learning Course

    Machine Learning

    Stanford / Computer Science
    Andrew Ng

Lectures

  1. The Motivation & Applications of Machine Learning Lecture
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    The Motivation & Applications of Machine Learning

    Stanford / Engineering
    Andrew Ng
  2. An Application of Supervised Learning - Autonomous Deriving Lecture
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    An Application of Supervised Learning - Autonomous Deriving

    Stanford / Computer Science
    Andrew Ng
  3. The Concept of Underfitting and Overfitting Lecture
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    The Concept of Underfitting and Overfitting

    Stanford / Engineering
    Andrew Ng
  4. Newton's Method Lecture
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    Newton's Method

    Stanford / Engineering
    Andrew Ng
  5. Discriminative Algorithms Lecture
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    Discriminative Algorithms

    Stanford / Computer Science
    Andrew Ng
  6. Multinomial Event Model Lecture
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    Multinomial Event Model

    Stanford / Computer Science
    Andrew Ng
  7. Optimal Margin Classifier Lecture
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    Optimal Margin Classifier

    Stanford / Computer Science
    Andrew Ng
  8. Kernels Lecture
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    Kernels

    Stanford / Engineering
    Andrew Ng
  9. Bias/variance Tradeoff Lecture
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    Bias/variance Tradeoff

    Stanford / Engineering
    Andrew Ng
  10. Uniform Convergence - The Case of Infinite H Lecture
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    Uniform Convergence - The Case of Infinite H

    Stanford / Computer Science
    Andrew Ng
  11. Bayesian Statistics and Regularization Lecture
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    Bayesian Statistics and Regularization

    Stanford / Computer Science
    Andrew Ng
  12. The Concept of Unsupervised Learning Lecture
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    The Concept of Unsupervised Learning

    Stanford / Computer Science
    Andrew Ng
  13. Mixture of Gaussian Lecture
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    Mixture of Gaussian

    Stanford / Engineering
    Andrew Ng
  14. The Factor Analysis Model Lecture
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    The Factor Analysis Model

    Stanford / Engineering
    Andrew Ng
  15. Latent Semantic Indexing (LSI) Lecture
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    Latent Semantic Indexing (LSI)

    Stanford / Computer Science
    Andrew Ng
  16. Applications of Reinforcement Learning Lecture
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    Applications of Reinforcement Learning

    Stanford / Computer Science
    Andrew Ng
  17. Generalization to Continuous States Lecture
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    Generalization to Continuous States

    Stanford / Engineering
    Andrew Ng
  18. State-action Rewards Lecture
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    State-action Rewards

    Stanford / Engineering
    Andrew Ng
  19. Advice for Applying Machine Learning Lecture
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    Advice for Applying Machine Learning

    Stanford / Computer Science
    Andrew Ng
  20. Partially Observable MDPs (POMDPs) Lecture
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    Partially Observable MDPs (POMDPs)

    Stanford / Computer Science
    Andrew Ng

Related Lectures

  1. GUI Lecture

    GUI

    Stanford / Engineering
    Mehran Sahami
  2. Hardware, Processors, and Implications for Software Lecture

    Hardware, Processors, and Implications for Software

    Harvard / Computer Science
    David J. Malan
  3. Security Introduction Lecture

    Security Introduction

    MIT / Engineering
    Hari Balakrishnan
  4. Creating a Generic Swap Function for Data Types of Arbitrary Size Lecture

    Creating a Generic Swap Function for Data Types of Arbitrary Size

    Stanford / Engineering
    Jerry Cain
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