Data science and machine learning is one of the world’s largest compute segment, in which small improvements in accuracy can translate into huge returns. To build the best models, data scientists work to train, evaluate, iterate, and retrain for highly accurate results and performant models. Want to learn how to engineer features and fit trees at lightning speed? This workshop focuses on performing data processing and machine learning using RAPIDS: a GPU-powered framework that enables massively parallel computations in typical data science workflows. Based on the familiar scikit-learn & pandas API, RAPIDS allows for an easy transition to GPU-powered systems and provides significant speed-ups in data processing and model development. With RA...
Deep learning models are trained on servers with many GPUs, andtraining must scale with the number o...
GPU technologies are the paradigm shift in modern computing. This book will take you through archite...
Training deep learning (DL) models is a highly compute-intensive task since it involves operating on...
Data science and machine learning is one of the world’s largest compute segment, in which small impr...
Data volumes and computational complexity of analysis techniques have increased, but the need to qui...
In recent years, proficiency in data science and machine learning (ML) became one of the most reques...
The invention of deep belief network (DBN) provides a powerful tool for data modeling. The key advan...
Map-Reduce is a framework for processing parallelizable problem across huge datasets using a large c...
Thesis (Ph.D.)--University of Washington, 2019Data, models, and computing are the three pillars that...
Deep Learning has become one of the most important tools in computer science in the last decade beca...
Mars-HD was built over Mars, a GPU MapReduce Framework, to allow it to work in the Hadoop cluster...
The ever growing body of digital data is challenging conventional analytical techniques in machine l...
To optimize the exploitation of oil and gas reservoirs both on- and offshore, Biodentfiy has develop...
Presented on September 6, 2016 from 1:00 p.m.-2:30 p.m. at the Klaus Advanced Computing Building, Ro...
We observe a continuously increased use of Deep Learning (DL) as a specific type of Machine Learning...
Deep learning models are trained on servers with many GPUs, andtraining must scale with the number o...
GPU technologies are the paradigm shift in modern computing. This book will take you through archite...
Training deep learning (DL) models is a highly compute-intensive task since it involves operating on...
Data science and machine learning is one of the world’s largest compute segment, in which small impr...
Data volumes and computational complexity of analysis techniques have increased, but the need to qui...
In recent years, proficiency in data science and machine learning (ML) became one of the most reques...
The invention of deep belief network (DBN) provides a powerful tool for data modeling. The key advan...
Map-Reduce is a framework for processing parallelizable problem across huge datasets using a large c...
Thesis (Ph.D.)--University of Washington, 2019Data, models, and computing are the three pillars that...
Deep Learning has become one of the most important tools in computer science in the last decade beca...
Mars-HD was built over Mars, a GPU MapReduce Framework, to allow it to work in the Hadoop cluster...
The ever growing body of digital data is challenging conventional analytical techniques in machine l...
To optimize the exploitation of oil and gas reservoirs both on- and offshore, Biodentfiy has develop...
Presented on September 6, 2016 from 1:00 p.m.-2:30 p.m. at the Klaus Advanced Computing Building, Ro...
We observe a continuously increased use of Deep Learning (DL) as a specific type of Machine Learning...
Deep learning models are trained on servers with many GPUs, andtraining must scale with the number o...
GPU technologies are the paradigm shift in modern computing. This book will take you through archite...
Training deep learning (DL) models is a highly compute-intensive task since it involves operating on...