evidently
flight-delay-notebooks
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| evidently | flight-delay-notebooks | |
|---|---|---|
| 10 | 1 | |
| 4,591 | 14 | |
| 3.3% | - | |
| 9.5 | 0.0 | |
| 7 days ago | over 1 year ago | |
| Jupyter Notebook | Jupyter Notebook | |
| Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
evidently
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Batch ML deployment and monitoring blueprint using open-source
Repo:https://github.com/evidentlyai/evidently/tree/main/examples/integrations/postgres_grafana_batch_monitoring
- Looking for recommendations to monitor / detect data drifts over time
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State of the Art data drift libraries on Python?
Thank you for your answer. I'm trying it today and the the other libraries mentioned + https://github.com/evidentlyai/evidently
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Package for drift detection
evidently: https://github.com/evidentlyai/evidently
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The hand-picked selection of the best Python libraries released in 2021
Evidently.
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[D] 5 considerations for Deploying Machine Learning Models in Production – what did I miss?
Consideration Number #5: For model observability look to Evidently.ai, Arize.ai, Arthur.ai, Fiddler.ai, Valohai.com, or whylabs.ai.
flight-delay-notebooks
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What's new in Elyra 2.0
Use the forum to ask general questions or share things you've created, like Nick Burdakous did. He recently published a pipeline viewer for Google Chrome and Mozilla Firefox. This viewer visualizes pipeline files on GitHub, like shown in the screen shot below. The depicted pipeline was created by Nick Pentreath and presented at the Big Things conference in November 2020.
What are some alternatives?
great_expectations - Always know what to expect from your data.
seldon-core - An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models
MLflow - Open source platform for the machine learning lifecycle
whylogs - 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. 📈
ydata-profiling - 1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
dvc - 🦉 ML Experiments and Data Management with Git
deepchecks - Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.
nannyml - nannyml: post-deployment data science in python
ML-Workspace - 🛠 All-in-one web-based IDE specialized for machine learning and data science.
bodywork-pipeline-with-aporia-monitoring - Integrating Aporia ML model monitoring into a Bodywork serving pipeline.
gradio - Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!
ml-pipeline-engineering - Best practices for engineering ML pipelines.