deepchecks VS shapash

Compare deepchecks vs shapash 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)

shapash

🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models (by MAIF)
Our great sponsors
  • WorkOS - The modern identity platform for B2B SaaS
  • InfluxDB - Power Real-Time Data Analytics at Scale
  • SaaSHub - Software Alternatives and Reviews
deepchecks shapash
15 8
3,295 2,629
2.7% 2.4%
8.6 8.6
6 days ago 7 days ago
Python Jupyter Notebook
GNU General Public License v3.0 or later 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.

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.

shapash

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

What are some alternatives?

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

shap - A game theoretic approach to explain the output of any machine learning model.

great_expectations - Always know what to expect from your data.

interpret - Fit interpretable models. Explain blackbox machine learning.

LIME - Tutorial notebooks on explainable Machine Learning with LIME (Original work: https://arxiv.org/abs/1602.04938)

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

trulens - Evaluation and Tracking for LLM Experiments

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.

GlassCode - This plugin allows you to make JetBrains IDEs to be fully transparent while keeping the code sharp and bright.

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]