Retail banking sample application showcasing Kubernetes and Google Cloud
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Updated
May 21, 2024 - Java
Retail banking sample application showcasing Kubernetes and Google Cloud
OpenRadioss is a powerful, industry-proven finite element solver for dynamic event analysis
DIY commercial datasets on Google Cloud Platform
Generate certificate suitable for use with any Kubernetes Mutating Webhook.
An inexpensive, autonomous, regolith-mining robot
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 responsibility
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 Indicator (RSI) is unreliable.
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.
Kubernetes metadata injection for New Relic APM to make a linkage between APM and Infrastructure data.
preCICE-adapter for the CFD code ANSYS Fluent (currently unmaintained)
PERIGEE is a finite element code for multiphysics analysis
Curated list of some open source codes employing isogeometric analysis (IGA)
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 of each match
Ingest sample retail data, build visualizations to explore past purchase behavior and use machine learning to predict the likelihood of future purchases
Use Databricks to improve the Claims Management process for faster claims settlement, lower claims processing costs and quicker identification of possible fraud
Mapping, Radial Basis Function, RBF, FSI
Perform fine-grained forecasting at the store-item level in an efficient manner, leveraging the distributed computational power of the Databricks Lakehouse Platform.
Shows how banks can modernize their risk management practices by back-testing, aggregating and scaling simulations by using a unified approach to data analytics with the Lakehouse.
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