Panel: The Great ML Language (Un)Debate! - #393

In a lively debate, Chris Nurenberger, a machine learning expert, champions Clojure for its conciseness. Barack Canberr pushes for JavaScript's accessibility, while Huda Nassar highlights Julia's speed and community. Robert Osizu-Aness discusses probabilistic programming's potential in NLP. Catherine Nelson emphasizes Python's flexibility, and Gabriella DeCuroz celebrates R's supportive resources. Avi Bryant discusses Scala's challenges, and Chris Lattner touts Swift's performance. Together, they explore the strengths and weaknesses of various programming languages in the ML landscape.