An inexpensive, autonomous, regolith-mining robot
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Updated
Aug 24, 2022 - Python
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
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
Ingest sample retail data, build visualizations to explore past purchase behavior and use machine learning to predict the likelihood of future purchases
Mapping, Radial Basis Function, RBF, FSI
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.
Equity Beta Calculation and CAPM
Preempt fraud with rule-based patterns and select ML algorithms for reliable fraud detection. Use anomaly detection and fraud prediction to respond to bad actors rapidly.
Using Apache tika and tesseract to extact text from any document
In this series of notebooks centered around geospatial analytics, we demonstrate how Lakehouse enables organizations to better understand customers behaviours, no longer based on who they are, but how they bank, no longer using a one-size-fits-all rule but a truly personalized AI
This series of notebooks shows how the Lakehouse for Financial Services enables banks, open banking aggregators and payment processors to address the challenge of merchant classification
Example scripts for the Python scripting API of the SimVascular FSI simulation tool wrote during Summer 2019 and Summer 2020 internships @ Stanford CBCL.
By applying transfer learning on pre-trained neural networks, we demonstrate how Databricks helps insurance companies kickstart their AI/Computer Vision journey towards claim assessment and damage estimation.
How to replace classical POD+I to do Real Time Aeroelasticity
In this regulatory reporting solution accelerator, we demonstrate how Delta Live Tables can guarantee the acquisition and processing of regulatory data in real time to accommodate regulatory SLAs. With Delta Sharing and Delta Live Tables combined, analysts gain real-time confidence in the quality of regulatory data being transmitted.
In this solution accelerator, we demonstrate a novel approach to consumer analytics by combining core mathematical concepts with engineering best practices and state of the art optimizations techniques to better model customers' behaviors and provide millions of customers with personalized insights
AML Solutions at Scale Using Databricks Lakehouse Platform
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