Building Data Products + Technology Implementation

Tonight, we will host our first remote Austin Deep Learning meetup. Please join us on Google Meet.

This month, Graham Ganssle from Expero will be walking us through building data products.

Data products are the scalable, reproducible outcomes of a data science workflow. We integrate data products into production systems serving high volume and/or high velocity use cases whether the end-users are customers, internal users, or downstream systems. Because data products depend not only on code but on data, building data products requires additional tooling than the traditional data science stack or the traditional software engineering stack. The four additional techniques are machine learning CI/CD, model monitoring, active learning, and interpretability. Because of these additional requirements demanded by these new techniques, data products sit at the intersection of data science, devops, and product strategy. Join us as Graham discusses the technological path to delivering data science insights and value to users in a productionized way through a deliberate, systematic delivery methodology we call Data Products.

Speaker Bio: Graham Ganssle is the Head of Data Science at Expero, Inc.

Agenda:

After the talk, we'll head over to CU29 (across the street from the Omni) for networking and deep learning discussions.

6:30 - 7:00: Networking and Announcements
7:00 - 8:00: Graham's Talk
8:00 - 8:30: Discussion and Networking

About our sponsors:

KUNGFU.AI (www.kungfu.ai) is an artificial intelligence agency, helping companies start and accelerate AI programs by providing strategy and development services.

Capital Factory (https://capitalfactory.com/) is the entrepreneurial center of gravity in Austin, Texas. Located in the middle of downtown, Capital Factory has more than 60,000 square feet full of startups and entrepreneurs. Take classes to learn the skills that startups need, attend meetups to find a co-founder, rent a desk for your startup or apply for funding and mentorship in the incubator and accelerator.