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 a beta 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
