Work done for University of Pittsburgh course "Principles of Data Science" (STAT 1261) with Dr. Junshu Bao in Fall semester of 2018.
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Updated
Jan 12, 2019 - R
Work done for University of Pittsburgh course "Principles of Data Science" (STAT 1261) with Dr. Junshu Bao in Fall semester of 2018.
Empirical Comparison of Regression Methods for Variability-Aware Performance Prediction. Эмпирическое сравние регрессионных методов для предсказания производительности конфигурируемых систем
In this repository, I've explored R programming, from basics to advanced concepts, for statistical models, data analysis, and data science. 📊🔍 Join me on this enriching journey! 🚀
Slides and code presented in the second meetup of R-Ladies Frankfurt
As part of a group project, I developed separate regression models using R to predict the daily number of batteries and robberies in Chicago using four different datasets. I tested interactive and second-order terms and used stepwise feature selection to find the best model with the given data. I tested several potential models using cross-valid…
Exploratory Data Analysis of Resume Names Dataset using R visualization packages
GIS Programming with Python Scripts. Functions: Automating Geoprocessing Tasks, Scripting Workflows, Data Management, Map Automation, Spatial Analysis and Batch Processing
Performed linear regression and residuals analysis on college tuition fees and admission rate in R.
This repository contains reproducible research on an epidemiological model for understanding COVID-19 spreading rates, as part of the DTU Data Science course 22100: R for Bio Data Science
In this project, an analysis of the investment process of the investor will be carried out. Data exploration, Data manipulation, Analysis of the investment process, Analyze the time until the first investment and Invest retention analysis
I use various techniques for analyzing the Stanford Congressional Records. Specifically, we will be looking at
Project and data courtesy of Datacamp. Taking a look at survey of tools used in data science.
This repository contains very messy data on the Billboard Top 100 from 2000. I am using this data set to improve at data cleaning / wrangling. The aim was to create a Cleveland Dot Plot which shows the progression of number 1 songs over time from that year.
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