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
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.
Data Pre-Processing
Data Reduction
Python Programming
Data Analysis
Data Visualization (DataViz)
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
Introduction to the project
Data Normalization and Clustering
Scatter Plot Matrix
Parallel coordinate plot
Data Reduction
Your workspace is a cloud desktop right in your browser, no download required
In a split-screen video, your instructor guides you step-by-step
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Yes, everything you need to complete your Guided Project will be available in a cloud desktop that is available in your browser.
You'll learn by doing through completing tasks in a split-screen environment directly in your browser. On the left side of the screen, you'll complete the task in your workspace. On the right side of the screen, you'll watch an instructor walk you through the project, step-by-step.
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