explainerdashboard VS deepchecks

Compare explainerdashboard vs deepchecks and see what are their differences.

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. (by deepchecks)
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explainerdashboard deepchecks
2 15
2,172 3,295
- 2.7%
8.0 8.6
11 days ago 6 days ago
Python Python
MIT License GNU General Public License v3.0 or later
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.

explainerdashboard

Posts with mentions or reviews of explainerdashboard. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-10-28.

deepchecks

Posts with mentions or reviews of deepchecks. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-06-18.

What are some alternatives?

When comparing explainerdashboard and deepchecks you can also consider the following projects:

great_expectations - Always know what to expect from your data.

model-validation-toolkit - Model Validation Toolkit is a collection of tools to assist with validating machine learning models prior to deploying them to production and monitoring them after deployment to production.

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

feast - Feature Store for Machine Learning

postgresml - The GPU-powered AI application database. Get your app to market faster using the simplicity of SQL and the latest NLP, ML + LLM models.

giskard - 🐢 Evaluation & Testing framework for LLMs and ML models

Activeloop Hub - Data Lake for Deep Learning. Build, manage, query, version, & visualize datasets. Stream data real-time to PyTorch/TensorFlow. https://activeloop.ai [Moved to: https://github.com/activeloopai/deeplake]

polyaxon - MLOps Tools For Managing & Orchestrating The Machine Learning LifeCycle

cleverhans - An adversarial example library for constructing attacks, building defenses, and benchmarking both

flyte - Scalable and flexible workflow orchestration platform that seamlessly unifies data, ML and analytics stacks.

shapash - 🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models

metaflow - :rocket: Build and manage real-life ML, AI, and data science projects with ease!