问题答疑
首页
实训课程
公开课
更多
首页
实训课程
公开课
扫码下载Android
扫码下载iOS
登录
首页
实训课程
公开课
登录
首页 - 课程列表 - 课程详情
返回
数据科学理论与应用
课程类型:
选修课
发布时间:
2023-07-18 10:55:44
主讲教师:
康乐乐
课程来源:
南京大学
建议学分:
0.00分
课程编码:
xtzx2371
课程介绍
课程目录
教师团队
1. Data Science Introduction
1.1 Data Science Introduction I-What is Data Science
(12分钟)
1.2 Data Science Introduction II- Data Science Product
(9分钟)
1.3 Data-Driven Decision Making
(10分钟)
1.4 Data Science is Interdisciplinary
(8分钟)
1.5 Course Design
(8分钟)
2. Data Types
2.1 Data Files and Data Types
(10分钟)
2.2 Rectangular Data and Nonrectangular Data
(9分钟)
2.3 Statistical Estimation in EDA
(12分钟)
2.4 Exploring numerical data
(10分钟)
2.5 Exploring categorical data
(10分钟)
3. R introduction
3.1 R introduction
(13分钟)
3.2 data structure
(8分钟)
3.3 Dplyr Package
(9分钟)
3.4 Tidyr Package
(8分钟)
3.5 Data Processing
(9分钟)
3.6 Data Transformation Tutorial
(11分钟)
4. Data Visualization
4.1 Data Visualization
(10分钟)
4.2 Basics of The ggplot2 Package
(9分钟)
4.3 Object and 7 Layers 上
(7分钟)
4.3 Object and 7 Layers 下
(7分钟)
4.4 ggplot2 practical operation-revised
(8分钟)
5. Regression
5.1 Definition of Linear Regression
(9分钟)
5.2 Ordinal Least Square Method
(10分钟)
5.3 Assumptions of OLS
(9分钟)
5.4 Tests and Intervals
(11分钟)
5.5 Multiple Linear Regressionn
(10分钟)
5.6 Model Evaluation
(10分钟)
5.7 Regression Tutorial
(10分钟)
6. Classification Algorithm
6.1.1 Basics of Classification
(7分钟)
6.1.2 Basics of Classification
(12分钟)
6.2 Logistic Regression
(10分钟)
6.3 Decision Tree
(10分钟)
6.4 Naive Bayes
(10分钟)
6.5 K-Nearest Neighbors
(10分钟)
6.6 classification practical operation
(9分钟)
7. Clustering Algorithm
7.1 Introduction 2.0
(9分钟)
7.2 Basics of Cluster 1.0
(8分钟)
7.3 Prototype-Based Clustering K-Means 1.0
(8分钟)
7.4 Density-Based Clustering DBSCAN and OPTICS 1.0
(10分钟)
7.5 Hierarchical Clustering Agnes and Diana 1.0
(9分钟)
7.6 Collaborative Filtering 1.0
(10分钟)
7.7 Cluster Model Tutorial
(9分钟)