High-dimensional Data visualization techniques using python

提供方
Coursera Project Network
在此指导项目中,您将:

Learn how to preprocess High-Dimensional data for visualization and analysis

Learn how implement Scatter plot matrix and Parallel Coordinate plot in python

Learn about why/how data reduction techniques

Clock2 hours
Intermediate中级
Cloud无需下载
Video分屏视频
Comment Dots英语(English)
Laptop仅限桌面

By the end of this project you will learn how to analyze high-dimensional data using different visualization techniques. We are going to learn how to implement Scatterplot Matrix and Parallel coordinate plots (PCP) in python. and We will learn how to use these two high-dimensional data visualization techniques to analyze our data by solving three tasks: Outlier Detection, Correlation Analysis and Cluster analysis. we will also talk about Data reduction techniques. we will learn how to sample our data to reduce the number of the data points for a better visualization. We will also learn about the Dimensionality reduction technique to reduce the number of dimensions in our dataset and how it can help us for a better analysis.

您要培养的技能

  • Data Pre-Processing
  • Data Reduction
  • Python Programming
  • Data Analysis
  • Data Visualization (DataViz)

分步进行学习

在与您的工作区一起在分屏中播放的视频中,您的授课教师将指导您完成每个步骤:

  1. Introduction to the project

  2. Data Normalization and Clustering

  3. Scatter Plot Matrix

  4. Parallel coordinate plot

  5. Data Reduction

指导项目工作原理

您的工作空间就是浏览器中的云桌面,无需下载

在分屏视频中,您的授课教师会为您提供分步指导

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