nannyml vs deep-significance

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)

#Machine Learning #ML #Mlops #Performance Monitoring #Data Science #Monitoring #Python #data-drift #model-monitoring #Data Analysis #Visualization #Deep Learning #jupyter-notebook #Machinelearning

Source Code

deep-significance

Enabling easy statistical significance testing for deep neural networks. (by Kaleidophon)

#significance-testing #Deep Learning #dl #hypothesis-testing #hypothesis-tests #statistical-significance #statistical-significance-test #Machine Learning #ML #Deeplearning #Machinelearning #compare-scores #deep-neural-networks

Source Code

deep-significance.rtfd.io

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nannyml		deep-significance
	Project
4	Mentions	6
1,362	Stars	275
8.1%	Growth	-
9.6	Activity	7.6
3 days ago	Latest Commit	3 months ago
Python	Language	Python
Apache License 2.0	License	GNU General Public License v3.0 only

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.

deep-significance

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

We haven't tracked posts mentioning deep-significance yet.
Tracking mentions began in Dec 2020.

What are some alternatives?

When comparing nannyml and deep-significance you can also consider the following projects:

Note - Note is a system for deep learning and reinforcement learning.

cuttle-cli - Cuttle automates the transformation of your Python notebook into deployment-ready projects (API, ML pipeline, or just a Python script)

evidently - Evaluate and monitor ML models from validation to production. Join our Discord: https://discord.com/invite/xZjKRaNp8b

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

ludwig - Data-centric declarative deep learning framework

barfi - Python Flow Based Programming environment that provides a graphical programming environment.

horovod - Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.

horovod - Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet. [Moved to: https://github.com/horovod/horovod]

eurybia - ⚓ Eurybia monitors model drift over time and securizes model deployment with data validation

clearml - ClearML - Auto-Magical CI/CD to streamline your ML workflow. Experiment Manager, MLOps and Data-Management

deep-significance vs Note

nannyml vs cuttle-cli

nannyml vs evidently

nannyml vs pandas-profiling