February Boston useR: Officer package & random mandalas deconstruction

February Boston useR Group

Officer Packager
Presented by Elizabeth (Libby) Heeren

Abstract: The officer package allows the manipulation of Microsoft Word and PowerPoint documents from R. Instead of typing up and knitting a markdown document and then formatting it later, it allows you to add paragraphs, graphs, and tables from data objects in R, all while keeping the custom styles in your desired Word or PowerPoint file. This parameterization of text and graphical elements can be immensely helpful when needing to create reports conforming to corporate reporting guidelines. The presentation will include a brief demo of Word and PowerPoint creation, as well as tips on getting started.

Speaker Bio: Libby is a decision scientist with a background in banking, insurance, tech, engineering, and supply chain. She has a deep affection for R and is passionate about reproducibility. She loves talking about all things data and hopes to encourage more women and underrepresented groups to join the data community.

Random mandalas deconstruction with R, Python, & Mathematica
Presented by Anton Antonov

Abstract: In this presentation we discuss the application of different dimension reduction algorithms over collections of random mandalas. We discuss and compare the derived image bases and show how those bases explain the underlying collection structure. The presented techniques and insights (1) are applicable to any collection of images, and (2) can be be included in larger, more complicated machine learning workflows. The former is demonstrated with a handwritten digits recognition application; the latter with the generation of random Bethlehem stars. The (parallel) walk-through of the core demonstration is in all three programming languages: Mathematica, Python, and R.

Speaker Bio: Anton is an applied mathematician (Ph.D.) with 30+ years of experience in algorithm development, scientific computing, mathematical modeling, natural language processing, combinatorial optimization, research and development programming, machine learning, and data mining. In the last ten years, he focused on developing machine learning algorithms and workflows for different industries (music, movies, recruiting, healthcare.)