Pablo Rodriguez's repositories
BERT-Legal-Classification
CaseText Court Case analysis with fine-tuned BERT Transformer
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
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
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
ReinforcementLearning
Grids, mountains, and mysterious problems. Solved with Partially-Observable Markov Decision Procesees. Created at Stanford University, by Pablo Rodriguez Bertorello
google-t5flan-finetune
This repository contains code for extending the Stanford Alpaca synthetic instruction tuning to existing instruction-tuned models such as Flan-T5.
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
TextSimplification-Tutorials
Sentence Simplification natural language algorithms
Challenge--FeatureColumnForClassification
Columns in TensorFlow modeling: numeric, bucketized, categorical, embedding, hashed, crossed
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
CustomerLifetimeValue
Customer Lifetime Value estimation model
Deep-Learning-Experiments
Notes and experiments to understand deep learning concepts
HeapAllocator
Enhancements on Bryant and O'Hallaron's Computer Systems
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
incubator-superset
Apache Superset is a Data Visualization and Data Exploration Platform
Kmeans-InitializationAlgorithms-EuclideanVsManhattan
A comparison of Random. vs Far centroid initialization, with Euclidean vs Manhattan distance
NaiveBayesVsLogisticRegression
A comparison of machine learning algorithms: Naive Bayes vs Logistic Regression. Created at Stanford University, by Pablo Rodriguez Bertorello
nanoGPT
The simplest, fastest repository for training/finetuning medium-sized GPTs.
Rapid-Reinforcement-Learning
The Courchevel environment eases the development of streaming Reinforcement Learning algorithms. Research at Stanford University, by Pablo Rodriguez Bertorello