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Unsupervised Learning | PCA and Clustering | Data Science with Marco

2020-06-30 Science & Technology
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Data Science with Marco
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Description

🐍Code: 6:30 Full notebook on Github: https://github.com/marcopeix/datasciencewithmarco/blob/master/Unsupervised%20Learning.ipynb In this video, we explore the concept of unsupervised learning by taking an in-depth look at principal component analysis (PCA) and clustering algorithms such as K-means. As always, we cover some theory and follow up with coding examples in Python. Like the video and subscribe to the channel for more data science content! Follow me on Medium: https://medium.com/@marcopeixeiro Coding examples inspired by the following scikit-learn examples: - Clustering: https://scikit-learn.org/stable/auto_examples/cluster/plot_color_quantization.html#sphx-glr-auto-examples-cluster-plot-color-quantization-py - PCA: https://scikit-learn.org/stable/auto_examples/decomposition/plot_pca_vs_lda.html

Top Comments (5)

@adinishad165 2020-07-14

make some video about time series..

3
@strawstraw1237 2023-10-09

Should we use the pc scores as the input for k-means or the original dataset?

1
@baharsh364 2021-05-11

Hey, You are talking about unsupervised learning PCA, But using the iris dataset with has all the target in it, I don’t understand how to plot the datasets without the target for PCA , as you have used y = iris_target, and use it in for loop to plot it!

1
@CarmenArlette 2022-11-15

Thank u very much!!

0
@Chaz.kitchen 2023-06-27

thanks a lot 😊😊😊

0

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