Dyalog APL for Data Science: From Basic Analysis to Materials Science Applications

Explore data science applications in Dyalog APL through this 18-minute conference talk that demonstrates the language's powerful capabilities for data analysis. Learn how APL primitives can solve introductory data science problems, comparing implementations with Python using classic datasets like Berkeley Admissions (1973) and Fisher's Iris Dataset (1936). Discover advanced Dyalog features for library development, including inverted tables, dynamic namespaces, and object-oriented programming. Follow along as real-world applications in materials science and microstructural analysis of metals are presented, showcasing APL's practical value in scientific computing. Gain insights into how APL's concise syntax and powerful primitives make it an effective tool for data scientists, complete with downloadable presentation slides for further reference.