Retail banking sample application showcasing Kubernetes and Google Cloud
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Updated
Oct 29, 2024 - Java
Retail banking sample application showcasing Kubernetes and Google Cloud
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DIY commercial datasets on Google Cloud Platform
Generate certificate suitable for use with any Kubernetes Mutating Webhook.
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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
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 Indicator (RSI) is unreliable.
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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
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.
Ingest sample retail data, build visualizations to explore past purchase behavior and use machine learning to predict the likelihood of future purchases
Perform fine-grained forecasting at the store-item level in an efficient manner, leveraging the distributed computational power of the Databricks Lakehouse Platform.
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