Design Considerations for building ML-Powered Search Applications

PyData Miami/NYC/Philly joint Meetup:

Design Considerations for building ML-Powered Search Applications

ABOUT:
Recent shifts to a remote economy have accelerated online commerce activities and the need to access remote information repositories. Information discovery is enabled through Search and Recommendations, but users expect Google-like quality results. In this talk, we discuss several ML strategies and design considerations around collecting and using signal data to train ranking algorithms and Collaborative Filtering recommenders as a component of a larger information portal. Recent progress in NLP and deep learning have ushered in a new wave of search methodologies, primarily vector-based search which is distinctly different from lexical-based search engines. We discuss how your businesses can leverage these advancements to drive a better user experience around information retrieval.

Agenda:
• 6:00pm - 6:30pm: Welcome and breakout sessions
• 6:30pm - 7:30pm: Talk: Design Considerations for building ML-Powered Search Applications

To get the most from this meetup, join the meeting with video and audio enabled so you can engage with other attendees! We will split into breakout sessions for informal chats then come back together for the talk.

Speakers:
Mark Moyou, PhD is currently a Senior Data Scientist at NVIDIA. Prior to NVIDIA, he was Data Science Manager at Lucidworks, a hyper-growth, San-Francisco based startup that delivers ML-powered search where he worked with Fortune 1000 clients on their Search and Recommendations roadmap for powering both external customer-facing and internal-facing search applications.

Jan Luke Moyou is a Data Scientist at Sohosquared, where he focuses on implementing end-to-end ML powered search applications for Fortune 1000 clients.

Hosted and sponsored by: PyData and Saturn Cloud