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The novel SMate approach leverages GAN minority-class image generators, which benefit from Transfer Learning from majority-class image generators. Consequently, SMate outperforms SMOTE for imbalanced image data-sets. Research at Stanford University, by: Pablo Rodriguez Bertorello, Liang Ping Koh

BERT-Legal-Classification

CaseText Court Case analysis with fine-tuned BERT Transformer

Jupyter Notebook

Bayesian-Structure-Learning

Search of an optimal Bayesian Network, assessing its best fit to a dataset, via an objective scoring function. Created at Stanford University, by Pablo Rodriguez Bertorello

Python

Image-Inventory-Reconciliation-with-SVM-and-CNN

Response to Amazon's Bin Image Data Set Challenge. Inventory reconciliation with machine learning: SVMs and CNNs. Research at Stanford University, by: Pablo Rodriguez Bertorello, Sravan Sripada, and Nutchapol Dendumrongsup

Jupyter Notebook

ReinforcementLearning

Grids, mountains, and mysterious problems. Solved with Partially-Observable Markov Decision Procesees. Created at Stanford University, by Pablo Rodriguez Bertorello

Julia