MLeap: Deploy ML Pipelines to Production
- scikit-learn
- spark
- data-pipelines
- transformers
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MLeap: Deploy ML Pipelines to Production
visual data prep powered by python
zerocode-tdd is a community-developed, free, open-source, outcome-driven automated testing framework for Data Pipelines, ETL, REST API, Kafka(Data Streams), Databases and Load scenarios. all defined in simple JSON or YAML — with zero coding.
🌊 Continuously synchronize the systems where your data lives, to the systems where you _want_ it to live, by managing your data flows with Estuary. 🌊
Pythonic tool for orchestrating machine-learning/high performance/quantum-computing workflows in heterogeneous compute environments.
Conduit streams data between data stores. Kafka Connect replacement. No JVM required.
Streaming reactive and dataflow graphs in Python
:mag: Data pipeline for crawling PDFs from the Web and transforming their contents into structured data using AWS textract. Built with AWS CDK + TypeScript
Build and deploy a serverless data pipeline on AWS with no effort.
Ordered-concurrently a library for concurrent processing with ordered output in Go. Process work concurrently and returns output in a channel in the order of input. It is useful in concurrently processing items in a queue, and get output in the order provided by the queue.
Reverse ETL for the code-first data stack
GTFS Data Pipeline for TfNSW Bus Datasets