cuML

Sep 25, 2025

How to GPU-Accelerate Model Training with CUDA-X Data Science

In previous posts on AI in manufacturing and operations, we covered the unique data challenges in the supply chain and how smart feature engineering can...
8 MIN READ
Sep 18, 2025

The Kaggle Grandmasters Playbook: 7 Battle-Tested Modeling Techniques for Tabular Data

Over hundreds of Kaggle competitions, we've refined a playbook that consistently lands us near the top of the leaderboard—no matter if we’re working with...
13 MIN READ
Decorative image of dark blue background with points of light connected with lines.
Sep 17, 2025

NVIDIA RAPIDS 25.08 Adds New Profiler for cuML, Updates to the Polars GPU Engine, Additional Algorithm Support, and More

The 25.08 release of RAPIDS continues to push the boundaries toward making accelerated data science more accessible and scalable with the addition of several...
9 MIN READ
Jul 17, 2025

Feature Engineering at Scale: Optimizing ML Models in Semiconductor Manufacturing with NVIDIA CUDA‑X Data Science

In our previous post, we introduced the setup of predictive modeling in chip manufacturing and operations, highlighting common challenges such as imbalanced...
6 MIN READ
Jun 18, 2025

AI in Manufacturing and Operations at NVIDIA: Accelerating ML Models with NVIDIA CUDA-X Data Science

NVIDIA leverages data science and machine learning to optimize chip manufacturing and operations workflows—from wafer fabrication and circuit probing to...
8 MIN READ
Picture of moss-covered trees in a forest.
Jun 05, 2025

Supercharge Tree-Based Model Inference with Forest Inference Library in NVIDIA cuML

Tree-ensemble models remain a go-to for tabular data because they're accurate, comparatively inexpensive to train, and fast. But deploying Python inference on...
11 MIN READ
May 22, 2025

Grandmaster Pro Tip: Winning First Place in a Kaggle Competition with Stacking Using cuML

What does it take to win a Kaggle competition in 2025? In the April Playground challenge, the goal was to predict how long users would listen to a podcast—and...
7 MIN READ
May 08, 2025

Spotlight: Accelerating the Discovery of New Battery Materials with SES AI's Molecular Universe

From the Stone Age to the digital era, materials have been the foundation of our civilization across all epochs. Today, finding new materials leads to progress...
7 MIN READ
May 07, 2025

Building Nemotron-CC, A High-Quality Trillion Token Dataset for LLM Pretraining from Common Crawl Using NVIDIA NeMo Curator

Curating high-quality pretraining datasets is critical for enterprise developers aiming to train state-of-the-art large language models (LLMs). To enable...
7 MIN READ
May 01, 2025

Stacking Generalization with HPO: Maximize Accuracy in 15 Minutes with NVIDIA cuML

Stacking generalization is a widely used technique among machine learning (ML) engineers, where multiple models are combined to boost overall predictive...
7 MIN READ
A diagram shows machine learning algorithms and the scikit-learn logo running on NVIDIA cuML to best leverage a system’s GPU and CPU.
Mar 18, 2025

NVIDIA cuML Brings Zero Code Change Acceleration to scikit-learn

Scikit-learn, the most widely used ML library, is popular for processing tabular data because of its simple API, diversity of algorithms, and compatibility with...
8 MIN READ
Jan 16, 2025

Accelerating Time Series Forecasting with RAPIDS cuML

Time series forecasting is a powerful data science technique used to predict future values based on data points from the past Open source Python libraries like...
4 MIN READ
Dec 12, 2024

Harnessing GPU Acceleration for Multi-Label Classification with RAPIDS cuML

Modern classification workflows often require classifying individual records and data points into multiple categories instead of just assigning a single label....
4 MIN READ
Nov 14, 2024

Faster Causal Inference on Large Datasets with NVIDIA RAPIDS

As consumer applications generate more data than ever before, enterprises are turning to causal inference methods for observational data to help shed light on...
4 MIN READ
Workflow diagram for disaggregating data into clusters and running in batches and merging.
Oct 31, 2024

Even Faster and More Scalable UMAP on the GPU with RAPIDS cuML

UMAP is a popular dimension reduction algorithm used in fields like bioinformatics, NLP topic modeling, and ML preprocessing. It works by creating a k-nearest...
12 MIN READ
Aug 29, 2024

Just Released: RAPIDS 24.08

RAPIDS 24.08 is now available with significant updates geared towards processing larger workloads and seamless CPU/GPU interoperability.
1 MIN READ