Dask Demo Day is getting closer, join us on Thursday 02/16 at 11am EST. We have a 5 great talks so far (see schedule on thread - pun intended) us06web.zoom.us/j/89383035703?…

Tip the scales with more speed and balance your datasets with cuML and imbalanced-learn resampling Nick Becker Dante Gama Dessavre Corey J Nolet medium.com/rapids-ai/fast…

Check out this detailed and fascinating new blog from the NVIDIA Merlin team! medium.com/nvidia-merlin/…

Are you in the financial service industry and looking to accelerate risk calculations? Check out how multiple GPUs on virtualized servers, leveraging NVIDIA AI Enterprise, can improve performance. #GPUacceleration #GTC23 bit.ly/3TwtLZD

Deutsche Bank details their #LLM journey and model training approach using Bert, FinFormer, GPT and T5, and strategy for model adaptation via fine-tuning and prompt learning using NeMo Megatron. Learn more in their #GTC23 session on March 23 at 9 AM PT. bit.ly/3Z2nSo4

How can financial services firms effectively detect fraudulent transactions across millions of endpoints? Mastercard is using transaction graph networks and #machinelearning to detect fraud. Join the #GTC23 session on March 22 at 10 AM ET. bit.ly/405GHYV

This week I spent some time debugging a problem that was discovered when using Apache Beam, on a Dask cluster with hundreds of NVIDIA GPUs. I thought it might be interesting to write up my debugging process for looking into bugs at this scale. jacobtomlinson.dev/posts/2023/deb…

Should I get my dog a puppy?

New in scikit-learn -- experimental support for building models on GPUs with PyTorch - Thomas J. Fan at #SciPy2023

Hello World

I'm excited to share that the RAPIDS 23.08 release adds support for CUDA 12 Conda packages! Thanks to all in the conda-forge community and at NVIDIA for help making this possible! medium.com/rapids-ai/rapi…

RAPIDS cuDF’s pandas accelerator mode is now available in open beta, accelerating #pandas nearly 150x with zero code changes. #DataScience, #Python, #RAPIDS Read the announcement blog: 👇 nvda.ws/469JnqC

🚀 Exciting News! 🚀 Thrilled to announce that @NVIDIA has joined scikit-learn @ La Fondation Inria as a corporate sponsor! 🤝💡 Their commitment to advancing open-source software in #MachineLearning is stronger than ever. Together, let's push the boundaries of innovation! bit.ly/3SJAT6z

Video of the explosion. Hope everyone was out of the house #Arlington #ballston Arlington Now @RealTimeNews10

Exactly one month ago I wrote a blog post about versioning software libraries by the amount of effort it takes to upgrade to a new version. jacobtomlinson.dev/effver/ Now EffVer has been adopted by Matplotlib! Wild! matplotlib.org/devdocs/devel/…

There are so many cool things in the new RAPIDS AI 24.02 release, but I think an under-appreciated one is the approach to deploy Dask on Databricks with GPUs! It's just so easy to run scale-out, GPU-accelerated Python now across all major clouds: medium.com/rapids-ai/rapi…

Together with NVIDIA RAPIDS we bring GPU acceleration to Polars! Read more in our release blog: pola.rs/posts/gpu-engi…

📣polars data GPU engine powered by RAPIDSai cuDF is now available in open beta. ⚡Accelerate Polars workflows up to 13x on NVIDIA GPUs. bit.ly/4dsrUgF

Today, PyData NYC 🗽 kicked off with a tutorial on GPU Accelerated Python! Numba, CuPy, and RAPIDS AI are all great ways to accelerate your code. Check out the full tutorial on the NVIDIA Accelerated Computing Hub to learn more: github.com/NVIDIA/acceler…

🙌 We’re excited to have Matthew Feickert, John Kirkham, and Ruben Arts teaching us "Reproducible Machine Learning Workflows for Scientists with pixi" at #SciPy2025! 🔥 Learn how to create fast, reliable, and reproducible ML environments using pixi, the next-gen package manager!