February 2020
Intermediate to advanced
37m
English
Closed Captioning available in German, English, Spanish, French, Japanese, Korean, Portuguese (Portugal, Brazil), Chinese (Simplified), Chinese (Traditional)
Overview
With the hype around artificial intelligence and machine learning sky high and the perceived talent shortage, it’s still extremely hard for organizations to build their machine learning efforts.
Madhura Dudhgaonkar (Workday) breaks down the lessons learned into an an actionable framework to bootstrap and scale a machine learning product function. You’ll see the framework in action through an actual 0 to 1 product journey, involving deep learning where value was delivered in record speed in spite of not having a dataset. You’ll hear counterintuitive tips that Madhura has been using to productize ML services over the last 5+ years (using a diverse range of technologies—vision, language, graph, anomaly detection, search relevance, and personalization).
Prerequisite knowledge
- A basic understanding of the machine learning discipline
What you'll learn
- See an actionable framework to begin and scale your ML product journey
- Discover tips on all sides of the equation for bootstrapping and scaling ML functions
This session is from the 2019 O'Reilly Artificial Intelligence Conference in San Jose, CA.
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