From 6ec8ee0dbeed24989077befed4d35ffe228a58da Mon Sep 17 00:00:00 2001 From: Dominik Moritz Date: Tue, 5 Aug 2025 13:53:52 +0200 Subject: [PATCH 1/3] docs: document upload and that embedding atlas supports embedding and projection --- packages/docs/algorithms.md | 2 +- packages/docs/overview.md | 4 ++++ 2 files changed, 5 insertions(+), 1 deletion(-) diff --git a/packages/docs/algorithms.md b/packages/docs/algorithms.md index bfe560e..a732da6 100644 --- a/packages/docs/algorithms.md +++ b/packages/docs/algorithms.md @@ -1,6 +1,6 @@ # Algorithms -The `embedding-atlas` package contains some useful algorithms regarding embeddings and clustering. +The `embedding-atlas` package contains some useful algorithms for computing embeddings and clustering. ## UMAP diff --git a/packages/docs/overview.md b/packages/docs/overview.md index dcac487..58c3dd8 100644 --- a/packages/docs/overview.md +++ b/packages/docs/overview.md @@ -2,6 +2,8 @@ Embedding Atlas is a tool that provides interactive visualizations for large embeddings. It allows you to visualize, cross-filter, and search embeddings and metadata. +You can use Embedding Atlas right from this website by [loading your own data](https://apple.github.io/embedding-atlas/upload/). Embedding Atlas will compute the embedding and projection right in your browser. Your data does not leave your machine. + Embedding Atlas is released as two packages: - A Python package `embedding-atlas` that provides: @@ -10,6 +12,8 @@ Embedding Atlas is released as two packages: - A [Jupyter widget](./widget.md) for using Embedding Atlas in Jupyter notebooks. - A [Streamlit component](./streamlit.md) for using Embedding Atlas in Streamlit apps. +All of these approaches allow you to compute embeddings (with custom models) and projections. + - An npm package `embedding-atlas` that exposes the user interface components as API so you can use them in your own applications. Below are the exposed components: - [Table](./table.md) From 1cb1e93645d02e2880013585fd687886ced534c5 Mon Sep 17 00:00:00 2001 From: Dominik Moritz Date: Tue, 5 Aug 2025 14:07:48 +0200 Subject: [PATCH 2/3] style: format --- packages/docs/overview.md | 2 -- 1 file changed, 2 deletions(-) diff --git a/packages/docs/overview.md b/packages/docs/overview.md index 58c3dd8..19dce6b 100644 --- a/packages/docs/overview.md +++ b/packages/docs/overview.md @@ -7,7 +7,6 @@ You can use Embedding Atlas right from this website by [loading your own data](h Embedding Atlas is released as two packages: - A Python package `embedding-atlas` that provides: - - A [command line utility](./tool.md) for running Embedding Atlas on a data frame. - A [Jupyter widget](./widget.md) for using Embedding Atlas in Jupyter notebooks. - A [Streamlit component](./streamlit.md) for using Embedding Atlas in Streamlit apps. @@ -15,7 +14,6 @@ Embedding Atlas is released as two packages: All of these approaches allow you to compute embeddings (with custom models) and projections. - An npm package `embedding-atlas` that exposes the user interface components as API so you can use them in your own applications. Below are the exposed components: - - [Table](./table.md) - [EmbeddingView](./embedding-view.md) - [EmbeddingViewMosaic](./embedding-view-mosaic.md) From 05df1ee46901610257e481d7ab53ad738b769cfa Mon Sep 17 00:00:00 2001 From: Fred Hohman Date: Tue, 5 Aug 2025 06:21:44 -0700 Subject: [PATCH 3/3] docs: minor word edits Remove double "right" --- packages/docs/overview.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/packages/docs/overview.md b/packages/docs/overview.md index 19dce6b..537867e 100644 --- a/packages/docs/overview.md +++ b/packages/docs/overview.md @@ -2,7 +2,7 @@ Embedding Atlas is a tool that provides interactive visualizations for large embeddings. It allows you to visualize, cross-filter, and search embeddings and metadata. -You can use Embedding Atlas right from this website by [loading your own data](https://apple.github.io/embedding-atlas/upload/). Embedding Atlas will compute the embedding and projection right in your browser. Your data does not leave your machine. +You can use Embedding Atlas directly from this website by [loading your own data](https://apple.github.io/embedding-atlas/upload/). Embedding Atlas will compute the embedding and projection in your browser. Your data does not leave your machine. Embedding Atlas is released as two packages: