r-programming

Implemented supply chain management scripting to optimize inventory classification and supplier management processes through the use of ABC segmentation and Kraljic Matrix.

A configurable installer CLI for installing R from source (sudo and non-sudo).

These materials support the Core statistics sessions, run through the Centre for Research Informatics Training at the University of Cambridge.

Simple Python and R tool for the purpose of swapping latinic letters with cirilic ones and vice versa in txt, docx and pdf files in Serbian language

A complete workflow for analyzing and visualizing bulk RNA-seq data.

A repo dedicated to learning machine learning in both Python and R

R Statistical Analysis Framework - Professional Python project

Chess.com web scraper, data analysis, and database examples

A data analysis mini project.

Implementing Gradient Boosting , XGboost, AdaBoost & SuperLearner in Python and comparing their classification accuracy of the two methods.

This project is the Udacity's A/B Testing final course project where a hypothetical experiment was conducted to test few metrics in the hypothetical online platform.

End-to-end SEC 13F institutional holdings data pipeline — download, parse, clean, and analyze filings from EDGAR using R, Quarto, SQLite, and Parquet.

Practice programming with R and Python on all data science algorithms

Materials supporting the Multivariate analysis sessions

Curso interactivo de R para Ciencias Sociales, construido con Quarto y WebR. Incluye 13 módulos, 89 ejercicios y desafíos con progreso local y sincronización opcional en Supabase.

Welcome to the Data Analysis and Econometrics repository! This space is dedicated to providing examples and snippets for applying econometric methods using various tools such as Python, R, GRETL, Excel, and more.

Daily recovery and strain insights using your Apple Watch data - built in 4 hours at Babson College Buildathon

Machine Learning with Python and R

Fit four different neural networks: (a) Two distinct single hidden layer neural networks. (b) Two distinct neural networks with two hidden layers. Compare the accuracy of these four Neural networks among them. Also compare it to other classification methods.