Equality AI Studio & EqualityML
Experience the potential of Human and Machine Intelligence with evidence-based fairness practices in MLOps
Equality AI Studio
One platform for all users
Accelerate development
- Evidence-based guidance for fair machine learning development in a collaborative environment
- Bias mitigation methods to "repair" datasets
- Model evaluation and parity adjustment on fairness metrics.
- 9 fairness metrics and 4 bias mitigation approaches to customize your approach.
- Low-code team environment to develop and govern fairness and bias mitigation experiments.
Collaborate
- Share and discover machine learning insights and models for cross-team collaboration.
- Create notebooks with integrated Equality AI and open-source frameworks and libraries.
- Review performance metrics and tradeoffs to engage stakeholders in the fairness evaluation and decision-making process with context for all audiences.
Secure and Compliant
Become an Equality AI Studio user and join our mission to end algorithmic bias!
Join nowEqualityML
Opensource python packages and Fair ML Learning
Experiment with Fair ML techniques
- Python packages for fair ML development and experimentation
- Fair ML learning and guidance
- Collaboration and contribution to the mission to end algorithmic bias
