This presentation presents a framework that data scientists can use to explain their black-box machine learning models in just a single line of code by using explainX.ai open-source library.

1. explainX.ai
EXPLAINABLE AI FRAMEWORK FOR MODEL DEVELOPERS
explainX.ai v1.0

2. PRODUCT VALUE
INCREASE
TRANSPARENCY
IMPROVE
MODEL
REMOVE
BIASES

3. HOW CAN WE MAKE INTERPRETABILITY
MORE ACCESSIBLE TO DATA SCIENTISTS,
ML ENGINEERS & RESEARCHERS?

4. explainX.ai
END-TO-END MODEL INTERPRETABILITY FRAMEWORK FOR MODEL DEVELOPERS
MODEL
AGNOSTIC
FAST &
EASY TO USE
EXTENSIVE EXPLAINABILITY
TECHNIQUES

5. explainX.ai
FEATURES
MODEL
EXPLAINABILITY
LOCAL PREDICTION
EXPLANATIONS
FEATURES
ANALYSIS
DATA
DISTRIBUTIONS

6. WHAT DOES THE EXPLAINX.AI OFFER?
ATTRIBUTION ALGORITHMS
+ SHAP (*)
+ LIME (*)
+ Integrated Gradients **
+ DeepLift **
FEATURE INTERACTION METHODS
+ PDPs (*)
+ What-If Analysis (*)
+ Data Distributions (*)
+ ALE Graphs (**)
+ Auto-Bias Detection (**)
RULES-BASED ALGORITHMS
+ ProtoDash (*)
+ Counterfactuals **
+ Decision Trees **
+ Anchors (Scoped Rules) **
explainX.ai Interactive Visualization Platform
+ Explaining & debugging model predictions
+ Sharing dashboards & actionable insights
(*) = Free Version
** = Pro Version

7. HOW CAN WE VISUALIZE &
EXPLAIN COMPLEX MODELS?

8. SINGLE API CALL
PRODUCT: explainX.ai v1.0
WEB APPLICATION ACCESSIBLE WITH A SINGLE API CALL
WATCH MVP DEMO

9. SINGLE API CALL
PRODUCT: explainX.ai v1.0
Any ML Model
Interactive and detailed
explanations
One Line of Code
In just a single line of code, data scientists can integrate our explainability module into their personal
workspace
EXPLAIN YOUR BLACKBOX MODEL NOW

10. VISUALIZING ATTRIBUTIONS OF A BLACK-BOX MODEL e.g. XGBoost, KNN

11. EXTRACT INFORMATION USING OUR INSIGHTS GENERATOR

12. SLICING INTO MODEL PREDICTIONS BY USING SQL

13. FEATURE INTERACTIONS USING A PDP PLOT

14. CHECK DISTRIBUTIONS FOR STATISTICALLY TROUBLESHOOTING DATA

15. SIMULATING MODEL BEHAVIOR BY TESTING VALUES IN A WHAT-IF FORM

16. CREATING EXAMPLES-BASED REASONING BY USING PROTOTYPES

17. CURRENT VERSION TRY IT OUT! FUTURE PIPELINE
Feature attribution based
algorithms.
Prototypes & examples based
algorithms
Feature interaction plots
An interactive platform for model
understanding & debugging
https://explainx.ai/register Adding more algorithms for
counterfactuals, anchors and bias
detection.
Scaling for enterprise adoption
Building support for complicated
deep learning models
Real-time monitoring

18. Thank you.
Questions?
Get in touch at raheel@explainx.ai