Retail banking sample application showcasing Kubernetes and Google Cloud
翻译 - Anthos零售银行示例应用程序
OpenRadioss is a powerful, industry-proven finite element solver for dynamic event analysis
The world's first CUDA implementation of Weakly-Compressible Smoothed Particle Hydrodynamics
DIY commercial datasets on Google Cloud Platform
Generate certificate suitable for use with any Kubernetes Mutating Webhook.
An inexpensive, autonomous, regolith-mining robot
#自然语言处理#In this solution, we offer a novel approach to sustainable finance by combining NLP techniques and news analytics to extract key strategic ESG initiatives and learn companies' commitments to corporate...
A highly available, 0-RPO FIX client and server implementation, used to demonstrate how stateful, long-lived processes can be created and managed easily with AWS managed services.
Using Google Cloud, this project is an example of how to detect anomalies in financial, technical indicators by modeling their expected distribution and thus inform when the Relative Strength Indicato...
Curated list of some open source codes employing isogeometric analysis (IGA)
preCICE-adapter for the CFD code ANSYS Fluent (currently unmaintained)
Kubernetes metadata injection for New Relic APM to make a linkage between APM and Infrastructure data.
PERIGEE is a finite element code for multiphysics analysis
Translating text attributes (like name, address, phone number) into quantifiable numerical representations Training ML models to determine if these numerical labels form a match Scoring the confidence...
Use Databricks to improve the Claims Management process for faster claims settlement, lower claims processing costs and quicker identification of possible fraud
A modular shared-memory high-performance framework for multiscale cardiac multiphysics simulations.
Perform fine-grained forecasting at the store-item level in an efficient manner, leveraging the distributed computational power of the Databricks Lakehouse Platform.
Ingest sample retail data, build visualizations to explore past purchase behavior and use machine learning to predict the likelihood of future purchases