Come and find out why and how to best use Kotlin for data science from the expert, Thomas Nield! We are very excited to be collaborating, for the first time, with the Chicago Kotlin Users Group (https://www.meetup.com/Chicago-Kotlin/).
As programmers, we love solving problems. But in the data science realm, we need more than programmer grit to solve many problems with no easy answer. Suppose you need to tightly schedule 190 classes in 20 classrooms, with different class durations, recurrences, and constraints throughout the week? What about minimizing the operating cost of a train schedule while maintaining a steady movement of passengers? How about anticipating an industry competitor's move? Or simply solving a Sudoku?
The data science space often uses platforms like Python and R, but the JVM is often where production actually happens. Kotlin might be able to close this gap, allowing data scientists to model towards production and not just prototypes. Come to this session to learn how Kotlin can position the JVM as a data science platform, and see live code examples of libraries and techniques for areas like discrete optimization, Bayesian analysis, and linear/nonlinear regression.
Thomas Nield (author of Getting Started with SQL and Learning RxJava) is a business consultant for Southwest Airlines. Early in his career, he became fascinated with technology and its role in business analytics. After becoming proficient in Java, Kotlin, Python, SQL, and reactive programming, he became an open-source contributor as well as an author/trainer for O’Reilly Media. He is passionate about sharing what he learns and enabling others with new skill sets. He enjoys making technical content relatable and relevant to those unfamiliar with or intimidated by it.
Currently, Thomas is interested in operations research, data science, and the Kotlin language. You may find him speaking on these three subjects and how they interconnect.
What to bring:
A government issued photo ID for building security.