A game theoretic approach to explain the output of any machine learning model.
- interpretability
- machine-learning
- deep-learning
- gradient-boosting
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A game theoretic approach to explain the output of any machine learning model.
End-to-end, code-first tutorials for building production-grade GenAI agents. From prototype to enterprise deployment.
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
optimization routines for hyperparameter tuning
⬛ Python Individual Conditional Expectation Plot Toolbox
InferPy: Deep Probabilistic Modeling with Tensorflow Made Easy
Using a Kalman Filter to interpolate bus position based on periodic measurements
Interpretable drug response prediction with graph neural networks over drugs, cell lines, and genes.