“Dimensionality reduction is a powerful tool for machine learning practitioners to visualize and understand large, high dimensional datasets. One of the most widely used techniques for visualization is t-SNE, but its performance suffers with large datasets and using it correctly can be challenging
“Dimensionality reduction is a powerful tool for machine learning practitioners to visualize and understand large, high dimensional datasets. One of the most widely used techniques for visualization is t-SNE, but its performance suffers with large datasets and using it correctly can be challenging
samurairodeo のブックマーク 2022/01/10 14:52
このブックマークにはスターがありません。
最初のスターをつけてみよう!
Understanding UMAP
pair-code.github.io2019/11/07
UMAP is a new dimensionality reduction technique that offers increased speed and better preservation of global structure.
12 人がブックマーク・1 件のコメント
\ コメントが サクサク読める アプリです /