实用机器学习

实用机器学习

文章目录

• 实用机器学习
• • 监督学习
  • • [Basic Concepts of Supervised Learning](#Basic Concepts of Supervised Learning)
    • [When should we use ML](#When should we use ML)
    • [What is a typical pipline of ML](#What is a typical pipline of ML)
    • [A toy example](#A toy example)
    • 改进
    • [Generalization 泛化](#Generalization 泛化)
    • 泛化：测试集上的表现
    • bias:
    • Variance:
    • [Define a ML problem](#Define a ML problem)
  • 无监督学习

监督学习

1. 分类
2. 回归

Basic Concepts of Supervised Learning

Sample，example, instance

Features, representations, predictiors

When should we use ML

What is a typical pipline of ML

Define A ML problem -> Construct Dataset -> Transform data &get features -> Design & train a model -> Use the model to predict

A toy example

1. Define a ML problem

   

2. Construct dataset

   

3. Transform data

   

4. Design % train a model(Training)

   

5. Use the model to predict

   

改进

Generalization 泛化

泛化：测试集上的表现

bias:

Variance:

Define a ML problem

无监督学习

1. 聚类
2. 降维