Machine Learning课程 by Andrew Ng

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大名鼎鼎的机器学习大牛Andrew Ng的Machine Learning课程,在此mark一下:



一:Coursera:

https://www.coursera.org/learn/machine-learning/home/info


这门课是Andrew Ng在其开创的公开在线课程网站coursera上最初开设的几门课之一,assignment也有一定的难度。大纲如下:

Syllabus

第 1周
Introduction
  • Environment Setup Instructions
  • Introduction
  • Review
  • Course Wiki Lecture Notes
  • Quiz: Introduction
  • 第 2周
    Linear Regression with One Variable
  • Model and Cost Function
  • Parameter Learning
  • Review
  • Quiz: Linear Regression with One Variable
  • 第 3周
    Linear Algebra Review
  • Linear Algebra Review
  • Review
  • 第 4周
    Linear Regression with Multiple Variables
  • Multivariate Linear Regression
  • Computing Parameters Analytically
  • Review
  • Quiz: Linear Regression with Multiple Variables
  • Programming Assignment: Linear Regression
  • 第 5周
    Octave Tutorial
  • Octave Tutorial
  • Submitting Programming Assignments
  • Review
  • Quiz: Octave Tutorial
  • 第 6周
    Logistic Regression
  • Classification and Representation
  • Logistic Regression Model
  • Multiclass Classification
  • Review
  • Quiz: Logistic Regression
  • Programming Assignment: Logistic Regression
  • 第 7周
    Regularization
  • Solving the Problem of Overfitting
  • Review
  • Quiz: Regularization
  • 第 8周
    Neural Networks: Representation
  • Motivations
  • Neural Networks
  • Applications
  • Review
  • Quiz: Neural Networks: Representation
  • Programming Assignment: Multi-class Classification and Neural Networks
  • 第 9周
    Neural Networks: Learning
  • Cost Function and Backpropagation
  • Backpropagation in Practice
  • Application of Neural Networks
  • Review
  • Quiz: Neural Networks: Learning
  • Programming Assignment: Neural Network Learning
  • 第 10周
    Advice for Applying Machine Learning
  • Evaluating a Learning Algorithm
  • Bias vs. Variance
  • Review
  • Quiz: Advice for Applying Machine Learning
  • Programming Assignment: Regularized Linear Regression and Bias/Variance
  • 第 11周
    Machine Learning System Design
  • Building a Spam Classifier
  • Handling Skewed Data
  • Using Large Data Sets
  • Review
  • Quiz: Machine Learning System Design
  • 第 12周
    Support Vector Machines
  • Large Margin Classification
  • Kernels
  • SVMs in Practice
  • Review
  • Quiz: Support Vector Machines
  • Programming Assignment: Support Vector Machines
  • 第 13周
    Unsupervised Learning
  • Clustering
  • Review
  • Quiz: Unsupervised Learning
  • 第 14周
    Dimensionality Reduction
  • Motivation
  • Principal Component Analysis
  • Applying PCA
  • Review
  • Quiz: Principal Component Analysis
  • Programming Assignment: K-Means Clustering and PCA
  • 第 15周
    Anomaly Detection
  • Density Estimation
  • Building an Anomaly Detection System
  • Multivariate Gaussian Distribution (Optional)
  • Review
  • Quiz: Anomaly Detection
  • 第 16周
    Recommender Systems
  • Predicting Movie Ratings
  • Collaborative Filtering
  • Low Rank Matrix Factorization
  • Review
  • Quiz: Recommender Systems
  • Programming Assignment: Anomaly Detection and Recommender Systems
  • 第 17周
    Large Scale Machine Learning
  • Gradient Descent with Large Datasets
  • Advanced Topics
  • Review
  • Quiz: Large Scale Machine Learning
  • 第 18周
    Application Example: Photo OCR
  • Photo OCR
  • Review
  • Conclusion
  • Quiz: Application: Photo OCR
  • 二:网易公开课(带中文翻译字幕、英文课件可打包下载):

    http://v.163.com/special/opencourse/machinelearning.html




    三:MOOC学院(类似于coursera):
    http://mooc.guokr.com/course/16/Machine-Learning/




    四:Stanford(斯坦福Machine Learning课程cs229.官网):
    http://cs229.stanford.edu/


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