Notes-ML-AndrewNg/notes/week1.md

• 1. 引言(Introduction)
• • 1.1 Welcome
  • 1.2 What is Machine Learning
  • 1.3 Supervised Learning
  • 1.4 Unsupervised Learning
• 2 Linear Regression with One Variable
• • 2.1 Model Representation
  • 2.2 Cost Function
  • 2.3 Cost Function - Intuition I
  • 2.4 Cost Function - Intuition II
  • 2.5 Gradient Descent
  • 2.6 Gradient Descent Intuition
  • 2.7 Gradient Descent For Linear Regression
• 3 Linear Algebra Review
• • 3.1 Matrices and Vectors
  • 3.2 Addition and Scalar Multiplication
  • 3.3 Matrix Vector Multiplication
  • 3.4 Matrix Matrix Multiplication
  • 3.5 Matrix Multiplication Properties
  • 3.6 Inverse and Transpose

1. 引言(Introduction)

1.1 Welcome

1.2 What is Machine Learning

1.3 Supervised Learning

1.4 Unsupervised Learning

2 Linear Regression with One Variable

2.1 Model Representation

2.2 Cost Function

2.3 Cost Function - Intuition I

2.4 Cost Function - Intuition II

2.5 Gradient Descent

2.6 Gradient Descent Intuition

2.7 Gradient Descent For Linear Regression

3 Linear Algebra Review

3.1 Matrices and Vectors

3.2 Addition and Scalar Multiplication

3.3 Matrix Vector Multiplication

3.4 Matrix Matrix Multiplication

3.5 Matrix Multiplication Properties

3.6 Inverse and Transpose