High-dimensional Data visualization techniques using python

提供方
Coursera Project Network
在此指導項目中,您將:

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中級
Cloud無需下載
Video分屏視頻
Comment Dots英語(English)
Laptop僅限桌面

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.

您要培養的技能

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

分步進行學習

在與您的工作區一起在分屏中播放的視頻中,您的授課教師將指導您完成每個步驟:

  1. Introduction to the project

  2. Data Normalization and Clustering

  3. Scatter Plot Matrix

  4. Parallel coordinate plot

  5. Data Reduction

指導項目工作原理

您的工作空間就是瀏覽器中的雲桌面,無需下載

在分屏視頻中,您的授課教師會為您提供分步指導

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