Initial PR of Docs migration by taureandyernv · Pull Request #837 · rapidsai/docs

taureandyernv · 2026-09-09T22:40:26Z

We will be

Removing the Contributing.MD Guide in favor of library level contribution guides
Editing the Visualization Guide
Editing the API guide
Editing the Index.md
Updating the naming of some libraries
Minor rearrangements of some libraries

One of the PRs needed for https://github.com/rapidsai/build-infra/issues/378

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bdice · 2026-09-09T23:03:51Z

+# NVIDIA Accelerated Data Science Featured User Guides

-The RAPIDS data science framework is a collection of libraries for running end-to-end data science pipelines completely on the GPU. The interaction is designed to have a familiar look and feel to working in Python, but utilizes optimized NVIDIA® CUDA® primitives and high-bandwidth GPU memory under the hood. Below are some links to help getting started with each of the individual RAPIDS libraries.
+The NVIDIA Data Science data science framework is a collection of libraries for running end-to-end data science pipelines completely on the GPU. The interaction is designed to have a familiar look and feel to working in Python, but utilizes optimized NVIDIA® CUDA® primitives and high-bandwidth GPU memory under the hood. Below are some links to help getting started with each of the individual libraries.


This says Data Science twice. Fix?

bdice · 2026-09-09T23:04:23Z


 **<i class="fa-solid fa-book-open"></i> [Community Notebooks](https://github.com/rapidsai/notebooks-contrib)**:
- A collection of examples and tutorials used to introduce new users to the features and capabilities of RAPIDS.
+ A collection of examples and tutorials used to introduce new users to the features and capabilities of NVIDIA Data Science.


I think we are trying to use “CUDA-X” branding and avoid making Data Science sound like a specific product. I’ll tag you offline.

ncclementi

I left quite a few comments, and suggestions, and pointed out a few broken links and replacements.

Mainly that we need to follow the approved guidance for the name changes, I pointed to some of the possible variations on how to do the renaming

ncclementi · 2026-09-09T22:51:25Z

+# NVIDIA Accelerated Data Science Featured User Guides

-The RAPIDS data science framework is a collection of libraries for running end-to-end data science pipelines completely on the GPU. The interaction is designed to have a familiar look and feel to working in Python, but utilizes optimized NVIDIA® CUDA® primitives and high-bandwidth GPU memory under the hood. Below are some links to help getting started with each of the individual RAPIDS libraries.
+The NVIDIA Data Science data science framework is a collection of libraries for running end-to-end data science pipelines completely on the GPU. The interaction is designed to have a familiar look and feel to working in Python, but utilizes optimized NVIDIA® CUDA® primitives and high-bandwidth GPU memory under the hood. Below are some links to help getting started with each of the individual libraries.


We need to follow the naming convention agreed. If you need a reference on how to replace things, see rapidsai/deployment#748 (comment)

ncclementi · 2026-09-09T22:55:08Z

-
-**<i class="fa-solid fa-database"></i> ETL and Dataframe Processing with [cuDF](https://github.com/rapidsai/cudf)**:
+**<i class="fa-solid fa-database"></i> ETL and Dataframe Processing with [cuDF](https://github.com/NVIDIA/cudf)**:
 Start with the [10 Minutes to cuDF and Dask-cuDF User Guide](/api/cudf/stable/user_guide/10min/). Modeled after 10 Minutes to Pandas, this is a short introduction to cuDF that is geared mainly for new users. The [cuDF User Guide](/api/cudf/stable/user_guide/index/) is generally very extensive and helpful.


Suggested change

Start with the [10 Minutes to cuDF and Dask-cuDF User Guide](/api/cudf/stable/user_guide/10min/). Modeled after 10 Minutes to Pandas, this is a short introduction to cuDF that is geared mainly for new users. The [cuDF User Guide](/api/cudf/stable/user_guide/index/) is generally very extensive and helpful.

Start with the [10 Minutes to cuDF and Dask-cuDF User Guide](https://docs.nvidia.com/cudf/latest/cudf/10min/). Modeled after 10 Minutes to Pandas, this is a short introduction to cuDF that is geared mainly for new users. The [cuDF User Guide](https://docs.nvidia.com/cudf/latest/cudf/) is generally very extensive and helpful.

ncclementi · 2026-09-09T22:56:00Z



-**<i class="fa-solid fa-code-branch"></i> Graph Analytics with [cuGraph](https://github.com/rapidsai/cugraph)**:
+**<i class="fa-solid fa-code-branch"></i> Graph Analytics with [cuGraph](https://github.com/NVIDIA/cugraph)**:


cugraph is not in the NVIDIA org at teh moement.

Suggested change

**<i class="fa-solid fa-code-branch"></i> Graph Analytics with [cuGraph](https://github.com/NVIDIA/cugraph)**:

**<i class="fa-solid fa-code-branch"></i> Graph Analytics with [cuGraph](https://github.com/rapidsai/cugraph)**:

ncclementi · 2026-09-09T22:57:55Z


-**<i class="fa-solid fa-code-branch"></i> Graph Analytics with [cuGraph](https://github.com/rapidsai/cugraph)**:
+**<i class="fa-solid fa-code-branch"></i> Graph Analytics with [cuGraph](https://github.com/NVIDIA/cugraph)**:
 Start with the [Easy Path](/api/cugraph/stable/basics/nx_transition/#easy-path-use-networkx-graph-objects-accelerated-algorithms) to use NetworkX graph objects with accelerated algorithms. Or, use [nx-cugraph](/api/cugraph/stable/nx_cugraph/nx_cugraph/) to use the NetworkX API with a zero code change GPU accelerated backend. There is also a general [cuGraph Introduction](/api/cugraph/stable/basics/cugraph_intro/).


I'm not sure this links exist anymore, we should probably find different ones.

ncclementi · 2026-09-09T23:00:26Z

-**<i class="fa-solid fa-bolt"></i> Accelerated Apache Spark with [Spark RAPIDS](https://nvidia.github.io/spark-rapids/)**:
- Start with [the Examples Repository](https://github.com/NVIDIA/spark-rapids-examples) for Spark related utilities and examples using the RAPIDS Accelerator, including ETL, ML/DL, and more. A good [overview](https://nvidia.github.io/spark-rapids/) is available on their docs introduction.
+**<i class="fa-solid fa-bolt"></i> Accelerated Apache Spark with [Spark cuDF](https://nvidia.github.io/spark-rapids/)**:
+ Start with [the Examples Repository](https://github.com/NVIDIA/spark-rapids-examples) for Spark related utilities and examples using the cuDF Accelerator, including ETL, ML/DL, and more. A good [overview](https://nvidia.github.io/spark-rapids/) is available on their docs introduction.


the examples repo redirects to https://github.com/NVIDIA/cudf-spark-examples

the github.io link for spark rapids seems to be very old docs, I believe the new ones are https://docs.nvidia.com/spark-rapids/user-guide/latest/

ncclementi · 2026-09-09T23:03:45Z

 # RAPIDS Documentation and Resources

-This site serves to unify the documentation for RAPIDS. Whether you're new to RAPIDS,
-looking to contribute, or are a part of the RAPIDS team, the docs here will help guide
-you. Visit [RAPIDS.ai](https://rapids.ai) for more information on the overall project.
+This site serves to unify the documentation for NVIDIA Acclerated Data Science Libraries. Whether you're new here,
+looking to contribute, or are a part of NVIDIA's Data Science team, the docs here will help guide
+you. Visit [the NVIDIA Accelerated Data Science site](https://www.nvidia.com/en-us/deep-learning-ai/solutions/data-science/) for more information on the overall project.



Use one of the options in rapidsai/deployment#748 (comment)

ncclementi · 2026-09-09T23:04:23Z

@@ -1,7 +1,7 @@
-# NVIDIA RAPIDS Documentation
+# NVIDIA Accelerated Data Science Documentation


Use one of the options in rapidsai/deployment#748 (comment)

ncclementi · 2026-09-09T23:04:27Z


 This repository contains the source for the
-[NVIDIA RAPIDS documentation site](https://docs.rapids.ai/). The site is built
+[NVIDIA Data Science documentation site](https://docs.rapids.ai/). The site is built


Use one of the options in rapidsai/deployment#748 (comment)

ncclementi · 2026-09-09T23:04:43Z

 ```

-This applies the RAPIDS library/version selectors to the imported documentation.
+This applies the NVIDIA Data Science library/version selectors to the imported documentation.


Use one of the options in rapidsai/deployment#748 (comment)

ncclementi · 2026-09-09T23:05:33Z


 Pull requests opened against `rapidsai/docs` are copied to a
-`pull-request/<number>` branch by the RAPIDS copy-PR bot. That branch runs the
+`pull-request/<number>` branch by the copy-PR bot. That branch runs the


I think this bot is still named the same

Suggested change

`pull-request/<number>` branch by the copy-PR bot. That branch runs the

`pull-request/<number>` branch by the RAPIDS copy-PR bot. That branch runs the

initial PR of dos migration

2a2d209

taureandyernv requested a review from a team as a code owner September 9, 2026 22:40

taureandyernv added the 2 - In Progress Currenty a work in progress label Sep 9, 2026

bdice reviewed Sep 9, 2026

View reviewed changes

ncclementi reviewed Sep 9, 2026

View reviewed changes

Update naming

705a486

	Start with the [10 Minutes to cuDF and Dask-cuDF User Guide](/api/cudf/stable/user_guide/10min/). Modeled after 10 Minutes to Pandas, this is a short introduction to cuDF that is geared mainly for new users. The [cuDF User Guide](/api/cudf/stable/user_guide/index/) is generally very extensive and helpful.
	Start with the [10 Minutes to cuDF and Dask-cuDF User Guide](https://docs.nvidia.com/cudf/latest/cudf/10min/). Modeled after 10 Minutes to Pandas, this is a short introduction to cuDF that is geared mainly for new users. The [cuDF User Guide](https://docs.nvidia.com/cudf/latest/cudf/) is generally very extensive and helpful.



		<i class="fa-solid fa-code-branch"></i> Graph Analytics with [cuGraph](https://github.com/rapidsai/cugraph):
		<i class="fa-solid fa-code-branch"></i> Graph Analytics with [cuGraph](https://github.com/NVIDIA/cugraph):

		@@ -1,7 +1,7 @@
		# NVIDIA RAPIDS Documentation
		# NVIDIA Accelerated Data Science Documentation

	`pull-request/<number>` branch by the copy-PR bot. That branch runs the
	`pull-request/<number>` branch by the RAPIDS copy-PR bot. That branch runs the

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