didemch
Data Analyst | Pursuing Master's degree @ UCLA | Python, SQL, R, A/B testing, Statistics, ML
Los Angeles
Pinned Repositories
didemch
Config files for my GitHub profile.
didemch.github.io
ElNino-Analysis-Python
In this project, I explore the the underlying patterns and drivers of El Niño events using Python.
Forecasting-Covid-Cases-in-R
Building a few linear models to predict 2-week ahead COVID-19 case counts.
Large_Data_Analysis
Exploring statistical methods and principles, with focus on those suitable for non- linear, spatio-temporal autocorrelated data and unsupervised machine learning tools, to effectively extract quantitative information from large climate and earth system science observational and model data.
Predicting-Economic-Mobility-in-R
Predicting economic mobility based on community characteristics using OLS, Ridge and Lasso regressions
Sales-Analysis-SQL
Analyzing Product Sales with SQL
Wine-Classification-in-R
Finding out whether it is possible to predict the quality of the wine using Random Forests, Neural Networks, Classification trees and other methods
didemch's Repositories
didemch/Sales-Analysis-SQL
Analyzing Product Sales with SQL
didemch/ElNino-Analysis-Python
In this project, I explore the the underlying patterns and drivers of El Niño events using Python.
didemch/Wine-Classification-in-R
Finding out whether it is possible to predict the quality of the wine using Random Forests, Neural Networks, Classification trees and other methods
didemch/didemch
Config files for my GitHub profile.
didemch/didemch.github.io
didemch/Forecasting-Covid-Cases-in-R
Building a few linear models to predict 2-week ahead COVID-19 case counts.
didemch/Large_Data_Analysis
Exploring statistical methods and principles, with focus on those suitable for non- linear, spatio-temporal autocorrelated data and unsupervised machine learning tools, to effectively extract quantitative information from large climate and earth system science observational and model data.
didemch/Predicting-Economic-Mobility-in-R
Predicting economic mobility based on community characteristics using OLS, Ridge and Lasso regressions