Podcasts Technology Datacast Episode 47: Math and Machine Learning In Pedestrian Terms with Luis Serrano

Episode 47: Math and Machine Learning In Pedestrian Terms with Luis Serrano

Published: Nov. 9, 2020, 4 p.m.

 Show Notes

  • (2:12) Luis shared how he got excited about learning mathematics and specialized in combinatorics.
  • (4:26) Luis discussed his experience studying Math for his Bachelor’s and Master’s degrees at the University of Waterloo  - where he took many courses in combinatorics and engaged in undergraduate research.
  • (5:59) Luis pursued his Ph.D. in Mathematics at the University of Michigan - where he worked on Schubert Calculus that intersects combinatorics and geometry (check out his Ph.D. dissertation).
  • (8:45) Luis distinguished the differences between doing research in mathematics and machine learning.
  • (11:33) Luis went over his time as a Postdoc Fellow and Lecturer at the University of Quebec at Montreal - where he was a member of the LaCIM lab (whose areas of research originating in Combinatorics and its relationships to Algebra and Computer Science) and taught classes in French.
  • (13:47) Luis explained why he left academia and got his job as a Machine Learning Engineer at Google in 2014.
  • (16:33) Luis discussed the engineering and analytical challenges he encountered as part of the video recommendations team at YouTube.
  • (19:58) Luis shared lessons he learned to transition from academia to industry.
  • (22:25) Luis went over his move to become the Head of Content for AI and Data Science at Udacity, alongside his online education passion.
  • (26:08) Luis explained Udacity's educational approach to course content design in various nano degree programs, including Machine Learning, Deep Learning, and Data Science.
  • (28:46) Luis unpacked his end-to-end process of making YouTube, where he teaches concepts in Machine Learning and Math in layman terms.
  • (31:01) Luis unpacked his statement, "Humans are bad at abstraction, but great at math," from his video “You Are Much Better At Math Than You Think.”
  • (34:46) Luis shared his 3 favorite Machine Learning videos: Restricted Boltzmann Machines, A Friendly Introduction to Machine Learning, and My Story with the Thue-Morse Sequence.
  • (37:18) Luis discussed the data science culture at Apple, where he spent one-year teaching machine learning to the employees and doing internal consulting in AI-related projects.
  • (39:06) Luis revealed his interest in quantum computing. He works as a Quantum AI Research Scientist at Zapata Computing, a quantum software company that offers computing solutions for industrial and commercial use.
  • (43:19) Luis mentioned the challenges of writing “Grokking Machine Learning” - a technical book with Manning planned to be published next year - like a mystery novel.
  • (46:12) Luis shared the differences between working in Silicon Valley and Canada.
  • (47:50) Closing segment.

His Contact Info

His Recommended Resources

Here are the codes for free eBook copies of Luis' book "Grokking Machine Learning": gmldcr-D659, gmldcr-2512, gmldcr-0752, gmldcr-30A2, gmldcr-01E8. Additionally, use the code poddcast19 to receive a 40% discount of all Manning products!