ACM Learning Webinars
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Break Into AI: A Q&A with Andrew Ng on Building a Career in Machine Learning
Andrew Ng will share tips and tricks on how to break into AI. He will discuss some of the most valuable skills for today's machine learning engineers, how to gain the experience to successfully switch careers, and how to build a habit of lifelong learning. He will also take questions from aspiring engineers and business professionals who want to work on AI-powered products.
ACM award winners, leading researchers, industry veterans, thought leaders, and innovators address today and tomorrow's hottest topics and issues in computing for busy practitioners, as well as educators, students, and researchers. Check out our archive of these ACM Learning Webinars, free for members and non-members alike.
Talks from some of the leading visionaries and bleeding-edge researchers in AI/ML: Fei-Fei Li on visual intelligence in computers and ImageNet; Eric Horvitz on AI solutions in the open world; and Tom Mitchell on using ML to study how the brain creates and represents language.
View the most recent ACM Learning Webinar, "The Bayesian Zig Zag: Developing Probabilistic Models Using Grid Methods and MCMC," on demand. The talk was presented by Allen Downey, Professor of Computer Science, Olin College. Continue the discussion and checkout further resources on ACM's Discourse Page.
View the ACM Learning Webinar, "Designing an ML-Minded Product and a Product-Minded ML System," on demand. Grace Huang, data science manager at Pinterest, led the discussion. Ankur Teredesai, co-founder and CTO of KenSci, moderated the talk and questions from the audience. Continue the discussion and check out further resources on ACM's Discourse Page.