databricks-industry-solutions
There are 6 repositories under databricks-industry-solutions topic.
- esg-scoring
databricks-industry-solutions / esg-scoring
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
Language:Python 43 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
Language:Python 18Unlocking the Power of Health Data With a Modern Data Lakehouse
Language:Python 17Time series knowledge graphs for cybersecurity
Language:Python 14Ingest sample retail data, build visualizations to explore past purchase behavior and use machine learning to predict the likelihood of future purchases
Language:Python 13Help augment diagnostic workflows with this Databricks Solution Accelerator for pathology image analysis. Now you can rapidly process thousands of whole slide images in minutes and use machine learning to automate the detection of metastasis.
Language:Python 12- smart-claims
Use Databricks to improve the Claims Management process for faster claims settlement, lower claims processing costs and quicker identification of possible fraud
Language:Python 12 Perform fine-grained forecasting at the store-item level in an efficient manner, leveraging the distributed computational power of the Databricks Lakehouse Platform.
Language:R 11Genome-wide association studies identify genetic variations associated with a target disease or trait. Researchers and clinicians can use this information to better detect, treat and prevent chronic health conditions. This Solution Accelerator notebook builds on top of Glow
Language:Python 11- medicare-risk-adjustment
Databricks and John Snow Labs Solution Accelerator for Medicare Risk Adjustment automates the extraction of undiagnosed member conditions from unstructured clinical notes with NLP models, improving downstream reimbursements.
Language:Python 10 - value-at-risk
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.
Language:Python 10 IOC matching for incident responders, threat hunters, detection engineers, and security engineers.
Language:Python 9Leverage the Databricks Solution Accelerator for DNS analytics to accelerate time to detection and response across petabytes of data. Tap into DNS traffic logs, enrich streaming threat intelligence, and apply advanced analytics to detect DNS abnormalities and prevent malicious attacks.
Language:Python 8Our joint Solution Accelerator with John Snow Labs automates the detection of sensitive information contained within unstructured data using NLP models for healthcare. Extracted data is stored within the Lakehouse, where teams can use the pre-trained models to easily remove, obfuscate or mask data for downstream analytics at massive scale.
Language:Python 8Overall Equipment Effectiveness: Performant and Scalable End-to-End Equipment Monitoring
Language:Python 7Preempt 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.
Language:Python 7From FHIR ingestion to patient outcomes analysis
Language:Python 7Connect the impact of marketing and your ad spend to sales. Efficiently pinpoint the impact of various revenue-generating marketing activities to understand what works best. Focus on the best-performing channels to optimize media mix and drive revenue.
Language:Python 7- quant-beta-capm
Equity Beta Calculation and CAPM
Language:Python 7 Digital twins are created using data derived from sensors (often IoT or IIoT) that are attached to or embedded in the original object. This data provides both structural and operational views of what happens to the object in real time, allowing engineers to monitor systems and model systems dynamics.
Language:Python 6To ensure ongoing drug safety, pharma companies need to monitor and report adverse drug events post-market launch. This accelerator extracts, processes and analyzes adverse drug events from real-world text data using NLP
Language:Python 5- digitization-documents
Using Apache tika and tesseract to extact text from any document
Language:Python 5 Generate oncology insights from real-world data using NLP. Once extracted, oncology data is enriched with useful information like ICD-10 codes and used to build powerful visualizations
Language:Python 5- parts-demand-forecasting
Perform demand forecasting at the part level rather than the aggregate level to minimize disruptions in your supply chain and increase sales. Manage material shortages and predict overplanning
Language:Python 5 - routing
Get started with our Solution Accelerator for Scalable Route Generation to optimize delivery routes and increase profitability
Language:Python 5 Create advanced customer segments to drive better purchasing predictions based on behaviors. Using sales data, campaigns and promotions systems, this solution helps derive a number of features that capture the behavior of various households. Build useful customer clusters to target with different promos and offers.
Language:Python 5Survival analysis is a collection of statistical methods used to examine and predict the time until an event of interest occurs. In this Solution Accelerator, learn how to use different survival analysis techniques for predicting churn and calculating lifetime value.
Language:Python 5Build a lakehouse for all your gamer data and use natural language processing techniques to flag questionable comments for moderation.
Language:Python 5Enabling Computer Vision Applications With the Data Lakehouse
Language:Python 4Deploying and Maintaining Models on the Edge in Manufacturing
Language:Python 4Use machine learning and the Databricks Lakehouse Platform for product matching that can be used by marketplaces and suppliers for various purposes. Resolve differences between product definitions and descriptions and determine which items are likely pairs and which are distinct across disparate data sets.
Language:Python 4- predicting-implied-volatilityLanguage:Python 4
Get started with our Solution Accelerator for Propensity Scoring to build effective propensity scoring pipelines that: Enable the persistence, discovery and sharing of features across various model training exercises Quickly generate models by leveraging industry best practices Track and analyze the various model iterations generated
Language:Python 4Create fine-grained and viable estimates of buffer stock for raw material, work-in-progress or finished goods inventory items that can be scaled across the supply chain. Free up working capital that would be tied up in inventory and reallocate to more productive uses.
Language:Python 4Using Delta Sharing to Democratize Insights Into Social Determinants of Health
Language:Python 4Build a wide-and-deep recommender with collaborative filters that takes advantage of patterns of repeat purchases to suggest both previously purchased and related products.
Language:Python 4