Kinetica in Motion

The Kinetica Blog
Zhe Wu
Zhe Wu

Working with RAPIDS Using Kinetica’s pyGDF Open Source API

With the rise of GPU computing, streamlining the processing of data on GPUs has become critical to increase the speed and efficiency of machine learning. The RAPIDS open source data library is based on the Apache Arrow specification that’s also …

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Ken Wattana
Ken Wattana

GPUs in Germany, a Recap from NVIDIA GTC Europe

Auf Wiedersehen Germany! Last week we wrapped up a highly successful GPU Technology Conference (GTC) Europe in Munich! GTC is NVIDIA’s international conference series, bringing together the top minds in deep learning, analytics, and of course GPUs for sessions, workshops, …

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Chad Juliano
Chad Juliano

Kinetica Sparse Data Tutorial

Introduction

This tutorial describes the application of Singular Value Decomposition or SVD to the analysis of sparse data for the purposes of producing recommendations, clustering, and visualization on the Kinetica platform. Sparse data is common in industry and especially in …

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Dipti Borkar
Dipti Borkar

Moving AI From Science Experiment To The Mainstream

For AI to become mainstream, it will need to move beyond small scale experiments run by data scientists ad hoc.

The complexity of technologies used for data-driven machine and deep learning means that data scientists spend less time developing algorithms …

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