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18 search results found
Prefect
⭐
14,603
Prefect is a workflow orchestration tool empowering developers to build, observe, and react to data pipelines
Flyte
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4,380
Scalable and flexible workflow orchestration platform that seamlessly unifies data, ML and analytics stacks.
Taipy
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4,311
Turns Data and AI algorithms into production-ready web applications in no time.
Lance
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3,003
Modern columnar data format for ML and LLMs implemented in Rust. Convert from parquet in 2 lines of code for 100x faster random access, vector index, and data versioning. Compatible with Pandas, DuckDB, Polars, Pyarrow, with more integrations coming..
Whylogs
⭐
2,533
An open-source data logging library for machine learning models and data pipelines. 📚 Provides visibility into data quality & model performance over time. 🛡️ Supports privacy-preserving data collection, ensuring safety & robustness. 📈
Traceml
⭐
490
Engine for ML/Data tracking, visualization, explainability, drift detection, and dashboards for Polyaxon.
Raptor
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136
Transform your pythonic research to an artifact that engineers can deploy easily.
Datachecks
⭐
117
Open Source Data Quality Monitoring.
Beneath
⭐
64
Beneath is a serverless real-time data platform ⚡️
Noronha
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56
DataOps framework for Machine Learning projects.
Space
⭐
36
Unified storage framework for the entire machine learning lifecycle
Data Engineering And Dataops
⭐
34
Duke MIDS: Data Engineering and DataOps Course
Cli
⭐
19
Polyaxon Core Client & CLI to streamline MLOps
Pipelime Python
⭐
18
A swiss army knife for data processing!
Smartpipeline
⭐
16
A framework for rapid development of robust data pipelines following a simple design pattern
Awesome Aiml Data Ops
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15
Awesome AI -ML-Data Ops
Devsquad Accelerators
⭐
13
Index repo listing all DevSquad accelerators templates, workshops, and hacks.
Awesome Ml Monitoring
⭐
11
A curated list of awesome open source tools and commercial products for monitoring data quality, monitoring model performance, and profiling data 🚀
Mastro
⭐
6
Metadata management in Go
Scalable Data Science
⭐
5
Scalable Data Science: The state of DataOps / MLOps in 2018
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