ML-Workspace
evidently
Our great sponsors
ML-Workspace | evidently | |
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7 | 10 | |
3,310 | 4,557 | |
1.3% | 4.6% | |
2.7 | 9.5 | |
5 months ago | about 23 hours 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.
ML-Workspace
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[D] I recently quit my job to start a ML company. Would really appreciate feedback on what we're working on.
Also check out: https://github.com/ml-tooling/ml-workspace, it a nice open source project with lots of packages ready to use.
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Dynamically spin up VM (based on specific HTTPS request) and stop it once session is over?
It will be a web based IDE dev kit (like Jupyter Hub, or JupyterLab) if you are familiar with them)
- Visual Studio Code now available as Web based editor for GitHub repos
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.
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. 📈
JupyterLab - JupyterLab computational environment.
ydata-profiling - 1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
Gitpod - DEPRECATED since Gitpod 0.5.0; use https://github.com/gitpod-io/gitpod/tree/master/chart and https://github.com/gitpod-io/gitpod/tree/master/install/helm
keytotext - Keywords to Sentences
self-hosted - Sentry, feature-complete and packaged up for low-volume deployments and proofs-of-concept
Code-Server - VS Code in the browser
cocalc-docker - DEPRECATED (was -- Docker setup for running CoCalc as downloadable software on your own computer)
dvc - 🦉 ML Experiments and Data Management with Git