python机器学习ch01

python机器学习

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Python Machine Learning - Code Examples

Chapter 1 - Giving Computers the Ability to Learn from Data

Overview

• Building intelligent machines to transform data into knowledge
• The three different types of machine learning
  • Making predictions about the future with supervised learning
    • Classification for predicting class labels
    • Regression for predicting continuous outcomes
  • Solving interactive problems with reinforcement learning
  • Discovering hidden structures with unsupervised learning
    • Finding subgroups with clustering
    • Dimensionality reduction for data compression
    • An introduction to the basic terminology and notations
• A roadmap for building machine learning systems
  • Preprocessing - getting data into shape
  • Training and selecting a predictive model
  • Evaluating models and predicting unseen data instances
• Using Python for machine learning
• Installing Python packages
• Summary

from IPython.display import Image

Building intelligent machines to transform data into knowledge

构建智能机器，来将数据转换为知识

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The three different types of machine learning

三种不同类型的机器学习

Image(filename='./images/01_01.png', width=500) 

Making predictions about the future with supervised learning

通过监督学习来预测未来

Image(filename='./images/01_02.png', width=500)  

# 设置一个单元格进行多个输出
from IPython.core.interactiveshell import InteractiveShell
InteractiveShell.ast_node_interactivity = 'all'

Classification for predicting class labels

预测类标签的所属类别

Image(filename='./images/01_03.png', width=300) 

Regression for predicting continuous outcomes

预测输出结果连续的回归

Image(filename='./images/01_04.png', width=300) 

Solving interactive problems with reinforcement learning

使用强化学习解决交互问题

Image(filename='./images/01_05.png', width=300)  # Agent技术是一种处于一定环境下包装的计算机系统，为实现设计目的，能在该环境下灵活的，自主的活动。

Discovering hidden structures with unsupervised learning

通过无监督学习来发现隐藏的结构

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Finding subgroups with clustering

通过聚类来发现子簇/群

Image(filename='./images/01_06.png', width=300) 

Dimensionality reduction for data compression

通过数据压缩实现降维

Image(filename='./images/01_07.png', width=500) 

An introduction to the basic terminology and notations

介绍基本的术语和符号

Image(filename='./images/01_08.png', width=500) 

A roadmap for building machine learning systems

构建机器学习系统的路线图

Image(filename='./images/01_09.png', width=700) 

Preprocessing - getting data into shape

预处理–使得数据成型

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Training and selecting a predictive model

选择和训练一个预测模型

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Evaluating models and predicting unseen data instances

评估模型，使用未知数据来进行预测

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Using Python for machine learning

使用python来进行机器学习

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Installing Python packages

安装python的（第三方）包

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Summary

摘要

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