pablo-tech Goto Github PK
Name: Pablo Rodriguez
Type: User
Company: Stanford University
Bio: Personalization engines for Fortune500. Natural Language at Stanford.
Twitter: pablo_tech
Location: Palo Alto
Name: Pablo Rodriguez
Type: User
Company: Stanford University
Bio: Personalization engines for Fortune500. Natural Language at Stanford.
Twitter: pablo_tech
Location: Palo Alto
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
CaseText Court Case analysis with fine-tuned BERT Transformer
Columns in TensorFlow modeling: numeric, bucketized, categorical, embedding, hashed, crossed
Investigation of neural network conditioning under regularization approaches including Stochastic Gradient Descent. Research at Stanford University, by: Jakub Dworakowski, and Pablo Rodriguez Bertorello
Customer Lifetime Value estimation model
Notes and experiments to understand deep learning concepts
This repository contains code for extending the Stanford Alpaca synthetic instruction tuning to existing instruction-tuned models such as Flan-T5.
Enhancements on Bryant and O'Hallaron's Computer Systems
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
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
Apache Superset is a Data Visualization and Data Exploration Platform
Keras documentation, hosted live at keras.io
A comparison of Random. vs Far centroid initialization, with Euclidean vs Manhattan distance
Instead of computing Singular Value Decomposition, which fits to no-rating as if zero-rating, machine learn rating matrix decomposition
A comparison of machine learning algorithms: Naive Bayes vs Logistic Regression. Created at Stanford University, by Pablo Rodriguez Bertorello
The simplest, fastest repository for training/finetuning medium-sized GPTs.
Comparison of Google's Page Rank vs Hubs and Authorities on the Internet
The Courchevel environment eases the development of streaming Reinforcement Learning algorithms. Research at Stanford University, by Pablo Rodriguez Bertorello
Reasoning and Acting (ReAct) distillation from GPT4 to a small open source model
Grids, mountains, and mysterious problems. Solved with Partially-Observable Markov Decision Procesees. Created at Stanford University, by Pablo Rodriguez Bertorello
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
Sentence Simplification natural language algorithms
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.