Presentation: Machine Learning 101

Track: Machine Learning for Developers

Location: Pacific LMNO

Duration: 4:10pm - 5:00pm

Day of week: Wednesday

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Abstract

n this session, I will talk about machine learning primitives and how a capabilities-based approach can help software engineers understand machine learning data products. I will briefly cover three main ML primitives (classification, similarity, clustering), and go in-depth into the process of leveraging one of those primitives in the context of GitHub's repository recommendation engine. You should come to this session if you want a practical introduction of product ideation process from an ML perspective.

Audience

  • Software engineers interested in building and shipping ML products
  • Product Managers interested in understanding the ML product ideation process

What you can expect

  • An understanding of a data product versus a machine learning data product
  • An introduction to the process of building ML products
  • Learn to identify opportunities where machine learning can super-charge a product
  • Short demos explaining some core ML primitives

Speaker: Omoju Miller

Machine Learning @GitHub

Omoju Miller is a Senior Machine Learning Engineer with Github. She has over a decade of experience in computational intelligence. In the past, she has co-led the non-profit investment in Computer Science Education for Google and served as a volunteer advisor to the Obama administration’s White House Presidential Innovation Fellows.

Find Omoju Miller at

Tracks

Monday, 11 November

Tuesday, 12 November

Wednesday, 13 November