Seaborn Heatmap | Pandas Python Machine Learning

In this video, you’ll learn about creating heatmaps using Seaborn. Seaborn is essential to Machine Learning! It allows you to create advanced plots to visualize your data. In this video, you’ll learn how to create a correlation matrix, create heatmap from correlation matrix to observe relationships between variables at hand, and customize your heatmap through colors, line color, and line width. After watching this video and learning several Seaborn commands/plots, there’s an activity right below this description for you to try out on your own using the skills you learned here. Enjoy!

SEABORN HEATMAPS ACTIVITY:

Import libraries and load one Seaborn in-built dataset of your choice. Create a correlation matrix, then create a heatmap from this matrix. Lastly, customize your heatmap by using different color schemes, line colors, and line widths.

TIMESTAMP:

00:00 Introduction & Recap of Last Video
00:19 Lesson Structure for Seaborn Heatmaps
00:38 Import libraries/dataset + set up for first plot
01:14 Create correlation matrix
01:33 Create heatmap from matrix to observe relationships between variables at hand
01:48 Customize heatmap
02:14 Explore colors
02:43 Explore line color
03:00 Explore line width
03:22 Recap of Current Video
03:36 Call-to-action: Seaborn Heatmaps

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[piujha]

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[rosellealmeida]

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[findajob]

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Amazing content you shared.I learned on how to create and customize heatmap in Seaborn. Thanks for sharing 😊

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