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Machine Learning课程 by Andrew Ng

發布時間:2025/3/21 28 豆豆
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大名鼎鼎的機器學習大牛Andrew Ng的Machine Learning課程,在此mark一下:



一:Coursera:

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


這門課是Andrew Ng在其開創的公開在線課程網站coursera上最初開設的幾門課之一,assignment也有一定的難度。大綱如下:

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:網易公開課(帶中文翻譯字幕、英文課件可打包下載):

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




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




四:Stanford(斯坦福Machine Learning課程cs229.官網):
http://cs229.stanford.edu/


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