From ad2bd2b65ce2af4463a83791f9a976901f749299 Mon Sep 17 00:00:00 2001 From: Ray Douglass Date: Wed, 6 Dec 2023 14:20:44 -0500 Subject: [PATCH] REL v23.12.00 release --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 2c9c7028be..34c0a41cfc 100644 --- a/README.md +++ b/README.md @@ -9,7 +9,7 @@ programming. In most cases, cuML's Python API matches the API from For large datasets, these GPU-based implementations can complete 10-50x faster than their CPU equivalents. For details on performance, see the [cuML Benchmarks -Notebook](https://github.com/rapidsai/cuml/tree/branch-23.04/notebooks/tools). +Notebook](https://github.com/rapidsai/cuml/tree/branch-23.12/notebooks/tools). As an example, the following Python snippet loads input and computes DBSCAN clusters, all on GPU, using cuDF: ```python @@ -74,7 +74,7 @@ neighbors = nn.kneighbors(df) For additional examples, browse our complete [API documentation](https://docs.rapids.ai/api/cuml/stable/), or check out our example [walkthrough -notebooks](https://github.com/rapidsai/cuml/tree/branch-23.04/notebooks). Finally, you +notebooks](https://github.com/rapidsai/cuml/tree/branch-23.12/notebooks). Finally, you can find complete end-to-end examples in the [notebooks-contrib repo](https://github.com/rapidsai/notebooks-contrib).