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Explore how APL programming language serves as a powerful tool for data science applications in this 30-minute conference talk from DYNA Fall 2025. Discover the fundamental importance of data science in today's technology landscape and learn how APL's array-oriented nature makes it particularly well-suited for statistical analyses, machine learning, and AI foundation work. Examine the complete data science workflow including data collection, structuring, cleansing, visualization, and summarization techniques using APL. Get hands-on demonstrations of TamStat for statistical analysis and APLearn for machine learning implementations, while understanding the advantages APL offers over traditional ML libraries. Master key APL operators including Key (⌸) and Stencil (⌺) for advanced data manipulation and analysis tasks. Gain insights from Josh David's experience as an APL consultant and his work developing APL tools for North American clients, making this essential viewing for programmers interested in leveraging APL's concise, expressive syntax for complex data science problems.
