DLSEI 3.0 Cohort 3 registration has been closed.

High-dimensional Data visualization techniques using python

Included with DLSEI 3.0

Guided Project

Learn, practice, and apply job-ready skills with expert guidance

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Guided project Level

Recommended experience

2.00 Hours

Learn at your own pace

Data Science

Domain

About this guided project

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.

What skills will you gain?

Dimensionality Reduction

Statistical Analysis

Data Analysis

Exploratory Data Analysis

Data Science