opardo
Data Scientist with strong background in Applied Mathematics
Columbia UniversitySan Francisco, CA
Pinned Repositories
academic_website
📝 Easily create a beautiful website using Academic, Hugo, and Netlify
adl-fall-19
banks
Web application made using Django. It optimizes the ROI of the investors, given the interest rate and the minimum and maximum investments for a group of banks. Author: Carlos Omar Pardo Gomez.
BlackLivesMatter
NLP Analysis of tweets about the murder of black people, which gave rise to the #BlackLivesMatter movement.
dlmRStan
R package. Bayesian linear model in a time series context (dynamic beta for each observation). Uses RStan to develop the MCMC algorithm. Author: Carlos Omar Pardo Gomez.
GPDPQuantReg
R Package. Bayesian and nonparametric quantile regression, using Gaussian Processes to model the trend, and Dirichlet Processes, for the error. Author: Carlos Omar Pardo Gomez.
KPIsHealth
Shiny app. Useful to explore trends in time series, particularly designed for KPIs estimated from survey data. Author: Carlos Omar Pardo Gomez.
SoccerLearning
We are employing CNNs and RNNs to predict what team has the ball possession in a soccer game. Final project for the Applied Deep Learning class (Fall 2019).
Thesis
Bachelor thesis: A Bayesian and Nonparametric Quantile Regression Model. Final PDF, TeX files and particular applications' code, using GPDP package. Author: Carlos Omar Pardo Gomez.
WARS
Wes Anderson Recommendation System. Using Factorization Machines, finds the users who are more likely to enjoy the Wes Anderson's movies, as well as the right film for them. Final project for the Personalization: Theory and Applications class (Columbia University, Fall 2018).
opardo's Repositories
opardo/GPDPQuantReg
R Package. Bayesian and nonparametric quantile regression, using Gaussian Processes to model the trend, and Dirichlet Processes, for the error. Author: Carlos Omar Pardo Gomez.
opardo/BlackLivesMatter
NLP Analysis of tweets about the murder of black people, which gave rise to the #BlackLivesMatter movement.
opardo/Thesis
Bachelor thesis: A Bayesian and Nonparametric Quantile Regression Model. Final PDF, TeX files and particular applications' code, using GPDP package. Author: Carlos Omar Pardo Gomez.
opardo/banks
Web application made using Django. It optimizes the ROI of the investors, given the interest rate and the minimum and maximum investments for a group of banks. Author: Carlos Omar Pardo Gomez.
opardo/dlmRStan
R package. Bayesian linear model in a time series context (dynamic beta for each observation). Uses RStan to develop the MCMC algorithm. Author: Carlos Omar Pardo Gomez.
opardo/SoccerLearning
We are employing CNNs and RNNs to predict what team has the ball possession in a soccer game. Final project for the Applied Deep Learning class (Fall 2019).
opardo/WARS
Wes Anderson Recommendation System. Using Factorization Machines, finds the users who are more likely to enjoy the Wes Anderson's movies, as well as the right film for them. Final project for the Personalization: Theory and Applications class (Columbia University, Fall 2018).
opardo/academic_website
📝 Easily create a beautiful website using Academic, Hugo, and Netlify
opardo/adl-fall-19
opardo/InsideTheOffice
R project. Exploratory data analysis and visualizations from The Office series (NBC). Final project for the EDAV class. (Columbia University, Fall 2018).
opardo/KPIsHealth
Shiny app. Useful to explore trends in time series, particularly designed for KPIs estimated from survey data. Author: Carlos Omar Pardo Gomez.
opardo/Atleta
OOP Python project. Hypothetical retirement plan for NFL players. Final project for the ITAM's Standards of Actuarial Practice class (Spring 2016).
opardo/dotfiles
My set of dotfiles. Includes Zsh, Bash, Git, iTerm, and OS X.
opardo/ModelosMatematicos
Repositorio personal de la clase impartida por el profesor José Luis Morales, ITAM 2015.
opardo/NYYDL2019
What were the odds of the 2019 New York Yankees injuries?
opardo/PythonMLWorkshop
Workshop part of the #DatatonXOberarzbacher series. We will focus on Applied Machine Learning in Python. Lecturer: Omar Pardo Gomez
opardo/website
📝 Easily create a beautiful website using Academic, Hugo, and Netlify