Apply Code UMAP 2022 - Dimensional Reduction of Embeddings w/ Python, Colab Jupyter NB
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Apply Code UMAP 2022 - Dimensional Reduction of Embeddings w/ Python, Colab Jupyter NB
Our SBERT (BI-encoder) data live in a high-dim vector space. But we want a 3D visualization. Therefore we use Python Library UMAP - Uniform Manifold Approximation and Projection for Dimension Reduction! An Introduction to dimensional reduction with classical UMAP, next video will focus on more advanced versions! Yes, finally! Topological ...
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AI | Machine Learning | Tech on Instagram: "UMAP (Uniform Manifold Approximation and Projection) is a dimensionality reduction technique used to simplify complex, high-dimensional data—making it easier to visualize in just 2 or 3 dimensions. Imagine you have a dataset that is difficult to understand since there are many features (such as height, age, weight, etc.). UMAP projects this data for visualization, in a 2D or 3D plot for instance. UMAP works by maintaining key spatial features and hiera
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AI | Machine Learning | Tech on Instagram: "UMAP (Uniform Manifold Approximation and Projection) is a dimensionality reduction technique used to simplify complex, high-dimensional data—making it easier to visualize in just 2 or 3 dimensions. Imagine you have a dataset that is difficult to understand since there are many features (such as height, age, weight, etc.). UMAP projects this data for visualization, in a 2D or 3D plot for instance. UMAP works by maintaining key spatial features and hiera
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