Market Basket Analysis: Shiny App
This Warehouse Dashboard application implements Market Basket Analysis to mine the relationship between different products. It uses 'arules' package for getting rules and 'flexdashboard' package for Shiny. https://skipper.shinyapps.io/shiny_warehouse_dashboard/?fbclid=IwAR14xXF60oytz55Vn-wcvMiDYsy_ky3kvKuVyj8o5OswEOuOeiMEBbLOHr4 The app tries to read the file 'data.zip' with 'data.csv' inside, if it exists in the working directory. Alternatevely, you may choose a local CSV-file that contains the columns: 'Date' (as yyyy-mm-dd), 'OrderID', 'ProductID', 'CustomerID', and 'Qty.Logged'.
About Me
Coherent professional with a problem-solving mentality accompanied by many years of researching and teaching experience in Ukrainian universities. With superior quality in data modeling and simulation, I am confident my work will exceed expectations [login to view URL] Specializing in: - Projects pertaining to Statistical/Data Analysis, Machine Learning, Mathematics, and Physics. - Open AI machine learning and natural language processing (NLP) techniques to analyze documents and respond user queries in a chatbot. - Consulting Businesses through Financial/Inventory/Customer Data Analysis and Forecast. Skills that pertain to this project are the following: - Excellent Communicator - Problem-solver - Attention to detail - Analytical Thinker Analysis Skills: - Multivariate Statistical Analysis - Regression Analysis - Factor Analysis & Sensitivity Analysis - Bayesian Analysis - Monte Carlo Analysis - Experimental Designs - Time Series Analysis - Forecasting - Statistical Quality Control - Spatial Data Analysis - Structural Equation Modeling. Program Proficiency: - Python - R programming - Rapidminer - Matlab - Microsoft Excel. I do not outsource my work; I am a one-man team. Mostly available from 9:00 to 19:00 GMT+2
