ExplainX is an explainable AI library for data scientists that enables them to explain, analyze and debug any black-box machine learning model - in just a single line of code.
We want data scientists to be more effective π in explaining model predictions to business stakeholders and building trustworthy AI solutions. πͺ
Our mission is to make a user-friendly, intuitive, and collaborative product for data science teams to enable explainable and resonsible AI. π
βπ©π»π»βπ¨π½π» Explain model predictions by identifying important features and their impact on the final outcome.
βπDebug machine learning models by understanding data distributions and the marginal effects of changing individual feature values.
βπ©π»Use the SQL module to dive into how model behavior changes with different subsets of your dataset. For example, the model might behave differently for different categories.
βπ¨ Business explanations by identifying similar profiles that support your model logic and are understood easily by your business stakeholder.
π¨ Use our what-if analysis and counterfactuals to play out different business scenarios and identify actionable recommendations for better business decision making.
Get in touch with us now: https://www.explainx.ai/contact-usβ
Check out our pricing: https://www.explainx.ai/pricingβ
βJoin our Slack community: https://www.explainx.ai/join-our-slack-communityβ