pablo-tech

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

BERT-Legal-Classification

CaseText Court Case analysis with fine-tuned BERT Transformer

google-t5flan-finetune

This repository contains code for extending the Stanford Alpaca synthetic instruction tuning to existing instruction-tuned models such as Flan-T5.

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

LatentFactorRecommendations

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

PageRank-vs-HubsAuthorities

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

reasoned-retrieval

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

ReinforcementLearning

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

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

TextSimplification-Tutorials

Sentence Simplification natural language algorithms

pablo-tech/BERT-Legal-Classification

CaseText Court Case analysis with fine-tuned BERT Transformer

pablo-tech/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

pablo-tech/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

pablo-tech/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

pablo-tech/ReinforcementLearning

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

pablo-tech/google-t5flan-finetune

This repository contains code for extending the Stanford Alpaca synthetic instruction tuning to existing instruction-tuned models such as Flan-T5.

pablo-tech/LatentFactorRecommendations

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

pablo-tech/PageRank-vs-HubsAuthorities

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

pablo-tech/reasoned-retrieval

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

pablo-tech/TextSimplification-Tutorials

Sentence Simplification natural language algorithms

pablo-tech/Challenge--FeatureColumnForClassification

Columns in TensorFlow modeling: numeric, bucketized, categorical, embedding, hashed, crossed

pablo-tech/Challenge--PredictShipCrewSize

pablo-tech/Conditioning-vs-Performance-in-Deep-Neural-Networks

Investigation of neural network conditioning under regularization approaches including Stochastic Gradient Descent. Research at Stanford University, by: Jakub Dworakowski, and Pablo Rodriguez Bertorello

pablo-tech/CustomerLifetimeValue

Customer Lifetime Value estimation model

pablo-tech/Deep-Learning-Experiments

Notes and experiments to understand deep learning concepts

pablo-tech/DeepThinkingBattleSnake

pablo-tech/HeapAllocator

Enhancements on Bryant and O'Hallaron's Computer Systems

pablo-tech/Huffman-Encoder-with-Trees-Heaps-Hashes

Implementation of David Huffman's 1952 Minimal-Redundancy Codes algorithm, one of the most cited papers in Computer Science. By Pablo Rodriguez Bertorello at Stanford University

pablo-tech/incubator-superset

Apache Superset is a Data Visualization and Data Exploration Platform

pablo-tech/keras-io

Keras documentation, hosted live at keras.io

pablo-tech/Kmeans-InitializationAlgorithms-EuclideanVsManhattan

A comparison of Random. vs Far centroid initialization, with Euclidean vs Manhattan distance

pablo-tech/NaiveBayesVsLogisticRegression

A comparison of machine learning algorithms: Naive Bayes vs Logistic Regression. Created at Stanford University, by Pablo Rodriguez Bertorello

pablo-tech/nanoGPT

The simplest, fastest repository for training/finetuning medium-sized GPTs.

pablo-tech/nanoGPT-colab

pablo-tech/QuestEval

pablo-tech/Rapid-Reinforcement-Learning

The Courchevel environment eases the development of streaming Reinforcement Learning algorithms. Research at Stanford University, by Pablo Rodriguez Bertorello

pablo-tech/TigerMarkovDecisionProblem