此课程重点介绍 MATLAB 中使用 Statistics Toolbox , Machine Learning ToolboxTM 和
Deep Learning ToolboxTM 功能的数据分析和机器学习技术。本课程
演示如何通过非监督学习发现大数据集的特点，以及通过监督学
习建立预测模型。课程中的示例和练习强调用于呈现和评估结果
的技巧。内容包括：
- 组织和预处理数据
- 聚类数据
- 创建分类模型
- 评估和改善模型
- 化简数据集
- 改善模型性能
- 详细课程提纲：
- 课程要求
- MATLAB 基础
- Importing and Organizing Data
- Objective: Bring data into MATLAB and organize it for analysis, including normalizing data and removing observations with missing values.
- · Data types
- · Tables
- · Categorical data
- · Data preparation
- Finding Natural Patterns in Data
- Objective: Use unsupervised learning techniques to group observations based on a set of explanatory variables and discover natural patterns in a data set.
- · Unsupervised learning
- · Clustering methods
- · Cluster evaluation and interpretation
- Building Classification Models
- Objective: Use supervised learning techniques to perform predictive modeling for classification problems. Evaluate the accuracy of a predictive model.
- · Supervised learning
- · Training and validation
- · Classification methods