DiCE VS MindsDB

Compare DiCE vs MindsDB and see what are their differences.

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DiCE MindsDB
2 78
1,270 21,223
2.1% 5.7%
8.2 10.0
10 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.

DiCE

Posts with mentions or reviews of DiCE. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-01-31.
  • [D] Have researchers given up on traditional machine learning methods?
    2 projects | /r/MachineLearning | 31 Jan 2023
    - all domains requiring high interpretability absolutely ignore deep learning at all, and put all their research into traditional ML; see e.g. counterfactual examples, important interpretability methods in finance, or rule-based learning, important in medical or law applications
  • [R] The Shapley Value in Machine Learning
    1 project | /r/MachineLearning | 25 Feb 2022
    Counter-factual and recourse-based explanations are alternative approach to model explanations. I used to work in a large financial institution, and we were researching whether counter-factual explanation methods would lead to better reason codes for adverse action notices.

MindsDB

Posts with mentions or reviews of MindsDB. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-03-24.

What are some alternatives?

When comparing DiCE and MindsDB you can also consider the following projects:

OmniXAI - OmniXAI: A Library for eXplainable AI

tensorflow - An Open Source Machine Learning Framework for Everyone

CARLA - CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms

H2O - H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

AIX360 - Interpretability and explainability of data and machine learning models

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.

interpret - Fit interpretable models. Explain blackbox machine learning.

CapRover - Scalable PaaS (automated Docker+nginx) - aka Heroku on Steroids

harakiri - Help applications kill themselves

scikit-learn - scikit-learn: machine learning in Python

stranger - Chat anonymously with a randomly chosen stranger

lightwood - Lightwood is Legos for Machine Learning.