Make Your Company Data Driven. Connect to any data source, easily visualize, dashboard and share your data.
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Updated
Aug 3, 2020 - JavaScript
Make Your Company Data Driven. Connect to any data source, easily visualize, dashboard and share your data.
Microsoft Machine Learning for Apache Spark
.NET for Apache® Spark™ makes Apache Spark™ easily accessible to .NET developers.
Apache Spark Connector for Azure Cosmos DB
Enabling Continuous Data Processing with Apache Spark and Azure Event Hubs
machine learning for genomic variants
Scalable Data Science, course sets in big data Using Apache Spark over databricks and their mathematical, statistical and computational foundations using SageMath.
Tools for Deploying Databricks Solutions in Azure
Testing framework for Databricks notebooks
code, labs and lectures for the course
MLFLow Tracking Server based on Docker and AWS S3
Collection of Sample Databricks Spark Notebooks ( mostly for Azure Databricks )
Collection of Machine Learning Examples for Azure Databricks
Terraform Databricks provider
(117th place - Top 26%) Deep learning using Keras and Spark for the "Store Item Demand Forecasting" Kaggle competition.
A solution for on-demand training and serving of Machine Learning models, using Azure Databricks and MLflow
A simplified, autogenerated API client interface using the databricks-cli package
Connect your Spark Databricks clusters Log4J output to the Application Insights Appender
A working example of DevOps & operationalisation applied to Machine Learning and AI
Spark stream consumption commit in kafka consumer group
Are you like me , a Senior Data Scientist, wanting to learn more about how to approach DevOps, specifically when you using Databricks (workspaces, notebooks, libraries etc) ? Set up using @Azure @databricks
VSTS Deployment Tasks for Databricks Objects
A Beginner's Guide to Azure Databricks
A DBAPI and SQLAlchemy dialect for interactive Databricks clusters.
OctopuFS library helps managing cloud storage, ADLSgen2 specifically. It allows you to operate on files (moving, copying, setting ACLs) in very efficient manner. Designed to work on databricks, but should work on any other platform as well.
MachineLearning examples using Spark MLIB and Databricks
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