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The Great ML Language (Un)Debate is the latest in our series of live discussion sessions. In this panel, we bring together experts and enthusiasts representing an array of both popular and emerging programming languages for machine learning. In this thoughtful discussion, we explore the strengths, weaknesses, and approaches offered by Clojure, JavaScript, Julia, Probabilistic Programming, Python, R, Scala, and Swift. We round out the session with an audience Q&A!
Thank you to IBM for their support in helping to make this panel possible! IBM is committed to educating and supporting data scientists and bringing them together to overcome technical, societal, and career challenges. Through the IBM Data Science Community site, which has over 10,000 members, they provide a place for data scientists to collaborate, share knowledge, and support one another.
IBM’s Data Science Community site is a great place to connect with other data scientists and to find information and resources to support your career.
Join and get a free month of select IBM Programs on Coursera.
Connect with our panelists:
- Clojure – Chris Nuernberger
- Managing Partner, TechAscent, LLC
- Connect with Chris on LinkedIn
- Javascript – Burak Kanber
- Author, “Machine Learning in Javascript”
- Follow Burak on Twitter
- Julia – Huda Nassar
- Postdoctoral Fellow, Stanford
- Follow Huda on LinkedIn
- Probabilistic Programming – Robert Osazuwa Ness
- Creator of Altdeep.AI
- Follow Robert on Twitter
- Python – Catherine Nelson
- Author, Building Machine Learning Pipelines
- Follow Catherine on Twitter
- R – Gabriela de Queiroz
- Scala – Avi Bryant
- Follow Avi on Twitter
- Swift – Chris Lattner
More will be added soon!
