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t.xlabel('Principal Component 1') plt.ylabel('Principal Component 2') plt.show() ``` t-SNE and UMAP Advanced techniques for visualization: ```python from sklearn.manifold import TSNE tsne = TSNE(n_components=2, perplexity=30, rand
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