nannyml VS evidently

Compare nannyml vs evidently and see what are their differences.

nannyml

Detecting silent model failure. NannyML estimates performance for regression and classification models using tabular data. It alerts you when and why it changed. It is the only open-source library capable of fully capturing the impact of data drift on performance. (by NannyML)

evidently

Evaluate and monitor ML models from validation to production. Join our Discord: https://discord.com/invite/xZjKRaNp8b (by evidentlyai)
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nannyml evidently
4 6
1,362 3,121
4.4% 3.0%
9.6 9.6
8 days ago 2 days ago
Python Python
Apache License 2.0 Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.

nannyml

Posts with mentions or reviews of nannyml. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning nannyml yet.
Tracking mentions began in Dec 2020.

evidently

Posts with mentions or reviews of evidently. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-05-24.

What are some alternatives?

When comparing nannyml and evidently you can also consider the following projects:

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

ydata-profiling - Create HTML profiling reports from pandas DataFrame objects

MLflow - Open source platform for the machine learning lifecycle

dvc - 🦉Data Version Control | Git for Data & Models | ML Experiments Management

flight-delay-notebooks - Analyzing flight delay and weather data using Elyra, IBM Data Asset Exchange, Kubeflow Pipelines and KFServing

bodywork-pipeline-with-aporia-monitoring - Integrating Aporia ML model monitoring into a Bodywork serving pipeline.

gradio - Create UIs for your machine learning model in Python in 3 minutes

NBA-attendance-prediction - Attendance prediction tool for NBA games using machine learning. Full pipeline implemented in Python from data ingestion to prediction. Attained mean absolute error of around 800 people (about 5% capacity) on test set.

whylogs - The open standard for data logging

ml-pipeline-engineering - Best practices for engineering ML pipelines.

ML-Workspace - 🛠 All-in-one web-based IDE specialized for machine learning and data science.