Coursera Machine Learning
by Stanford University

Table of Content

• WEEK 1

  • Linear Regression with One Variable
  • Linear Algebra Review

• WEEK 2

  • Linear Regression with Multiple Variables

• WEEK 3

  • Logistic Regression, Regularization

• WEEK 4

  • Neural Networks: Representation (Multi-class Classification and Neural Networks)

• WEEK 5

  • Neural Networks: Learning

• WEEK 6 (Regularized Linear Regression and Bias v.s. Variance)

  • Advice for Applying Machine Learning
  • Machine Learning System Design

• WEEK 7

  • Support Vector Machines

• WEEK 8

  • Unsupervised Learning
  • Dimensionality Reduction
  • (K-means Clustering and Principal Component Analysis)

• WEEK 9

  • Anomaly Detection and Recommender Systems

• WEEK 10

  • Large Scale Machine Learning

• WEEK 11

  • Application Example: Photo OCR