Corey Nolet

Corey Nolet is a Data Scientist & Sr. Engineer on the RAPIDS ML team at NVIDIA, where he focuses on building and scaling machine learning algorithms to support extreme data loads at light speed. Prior to working at NVIDIA, Corey spent over a decade building massive-scale exploratory data science & real-time analytics platforms for big-data and HPC environments in the defense industry. Corey holds Bs. & Ms. degrees in Computer Science. He is also working towards his Ph.D. in the same discipline, focused on the acceleration of algorithms at the intersection of graph and machine learning. Corey has a passion for using data to make better sense of the world.
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Posts by Corey Nolet

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Data Science

Reusable Computational Patterns for Machine Learning and Data Analytics with RAPIDS RAFT

RAPIDS is a suite of accelerated libraries for data science and machine learning on GPUs: cuDF for pandas-like data structures, cuGraph for graph data, and cuML... 11 MIN READ
Data Science

Faster HDBSCAN Soft Clustering with RAPIDS cuML

HDBSCAN is a state-of-the-art, density-based clustering algorithm that has become popular in domains as varied as topic modeling, genomics, and geospatial... 9 MIN READ
Accelerating classification on sparse data with GPUs and a splash of Bayes
Data Science

Faster Text Classification with Naive Bayes and GPUs

Naive Bayes (NB) is a simple but powerful probabilistic classification technique that parallelizes well and can scale to datasets of massive size.  If you... 11 MIN READ
Data Science

GPU-Accelerated Hierarchical DBSCAN with RAPIDS cuML – Let’s Get Back To The Future

Data scientists across various domains use clustering methods to find naturally ‘similar’ groups of observations in their datasets. Popular clustering... 10 MIN READ
Data Science

Analyzing the RNA-Sequence of 1.3M Mouse Brain Cells with RAPIDS on NVIDIA GPUs

Single-cell genomics research continues to advance drug discovery for disease prevention. For example, it has been pivotal in developing treatments for the... 8 MIN READ