Discover pablo-tech/Image-Inventory-Reconciliation-with-SVM-and-CNN

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pablo-tech

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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

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CaseText Court Case analysis with fine-tuned BERT Transformer

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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

SMate--SyntheticMinorityAdversarialTechnique

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

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ReinforcementLearning

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

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Sentence Simplification natural language algorithms

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PageRank-vs-HubsAuthorities

Comparison of Google's Page Rank vs Hubs and Authorities on the Internet

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LatentFactorRecommendations

Instead of computing Singular Value Decomposition, which fits to no-rating as if zero-rating, machine learn rating matrix decomposition

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reasoned-retrieval

Reasoning and Acting (ReAct) distillation from GPT4 to a small open source model

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pablo-tech/Image-Inventory-Reconciliation-with-SVM-and-CNN

pablo-tech

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