Developer Blog: Accelerating Python for Exotic Option Pricing

AI / Deep Learning, Featured, Financial Services

Nadeem Mohammad, posted Mar 18 2020

In this technical article, Yi Dong, a Deep Learning Solutions Architect at NVIDIA with a role to provide Financial Service Industry AI solutions, explores how to use Python GPU libraries to achieve the state-of-the-art performance in the domain of e

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Introduction to GPU Accelerated Python for Financial Services

Data Science, Financial Services, Machine Learning & Artificial Intelligence

Nadeem Mohammad, posted Jul 16 2019

Quantitative finance is commonly defined as the use of mathematical models and large datasets to analyze financial markets and securities.

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NVIDIA DGX-2 Helps Accelerates Key Algorithm for Hedge Funds by 6,000x

Artificial Intelligence / Deep Learning, Data Science, Features, HPC, DGX, Financial Services, Machine Learning & Artificial Intelligence

Nadeem Mohammad, posted May 13 2019

NVIDIA just broke the previous benchmarks of a key algorithm used by hedge funds to backtest trading strategies.

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On Demand Webinar: Deep Learning Demystified

Artificial Intelligence, Features, Automotive, Financial Services, Healthcare & Life Sciences, Machine Learning & Artificial Intelligence, Retail/Etail, webinar

Nadeem Mohammad, posted Mar 06 2018

Artificial Intelligence (AI) is solving problems that seemed well beyond our reach just a few years back.

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A New STAC-A2 Record

Accelerated Computing, Data Center, Financial Services, Tesla

Nadeem Mohammad, posted Nov 13 2017

The results are in, and GPUs are still the fastest solution on the planet for financial risk management. This is according to the latest STAC-A2 audited test results.

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Deep Learning Hyperparameter Optimization with Competing Objectives

Research, Financial Services, Machine Learning & Artificial Intelligence

Nadeem Mohammad, posted Aug 07 2017

Learn how to use SigOpt’s Bayesian optimization platform to jointly optimize competing objectives in deep learning pipelines on NVIDIA GPUs more than ten times faster than traditional approaches like random search.

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