Julia for AI and Data Science
Julia is a programming language with a set of features and a package ecosystem that makes it especially useful for AI/ML and data science. While the language is relatively young (measured in programming language years) the productivity it brings means that there is already a number of mature packages that push the state-of-the-art forward in domains such as differentiable programming, simulation, and optimization.In this talk, we will give a high-level overview of Julia with an emphasis on features, tools, and packages that makes it suitable for a typical AI/ML and data-science workflow. We will also give some examples of ongoing research done in Julia such as differentiable programming and automatic surrogatization for increased productivity in simulation and model-based workflows.
Kristoffer is a Chalmers University of Technology alumn who works at Julia Computing to develop the Julia language and the surrounding tooling. He is the current release manager and also works on the Julia package manager, the Julia debugger, and various other Julia tools.
