What we're about

The UX + Data Meetup explores the experience around data itself - how to make data easier to work with, how to get more value out of data, and how data enriches our work and lives.

Upcoming events (2)

Designing for Machine Learning Data Labeling

General Assembly

$10.00

***Please note our new location is at the General Assembly location on Broadway, 4th Floor*** Machine Learning at its most basic is the practice of using algorithms to parse data, learn from it, and then make a determination or prediction about something in the world. - NVIDIA Algorithmic performance can be highly impacted by the quality of input training data and the labels that are applied to that data. As they say, “Garbage in, garbage out”. However, getting high-quality inputs is easier said than done and is one large limitation in machine learning today. How can you get a high-quality labeled dataset? There are different approaches that depend on the project complexity, the training data, the size of the data science team, and the resources a company can allocate to data science projects. Different forms include labeling using internal teams, outsourcing, crowdsourcing, synthetic labeling and data programming. In this talk, Sabrina Siu will give a brief overview of these different techniques and use a case study to demonstrate obtaining high quality labels for messy datasets. She will also explore using data visualizations to explain machine learning results and lessons learned throughout this process. Speaker Bio Sabrina Siu is a product designer based in New York City. She currently works as a Product Designer at Augury, a machine learning startup, where she focuses on combining principles of design and user behavior to create a compelling predictive platform. Agenda: - Pizza and socializing begins @ 6:45 - Talk begins @ 7:00 followed by Q&A - A little extra socializing after the event

Data That Works – Building a Successful Analytics Practice

General Assembly

$10.00

***Please note our new location is at the General Assembly location on Broadway, 4th Floor*** WW (formerly Weight Watchers) may be 55 years old, but it has become a tech-enabled, data-rich, science-led powerhouse. Data and analytics now flow throughout all member touchpoints, including app and in-person, to create measurable improvements in their program, brand, and their members' lives. Michelle Glaser has built an analytics team and practice at WW by working closely with product and design to make data-driven decisions for product changes and improvements. Michelle will share how her team also coordinated with all areas of the organization from engineering to marketing to finance. Come hear about WW's transformation and how you can apply lessons they learned to your organization. Speaker Bio Michelle Glaser is an analytics leader who has built the analytics team and culture at WW. She is an epidemiologist turned analyst who has a passion for numbers that enables her to effectively build and drive global analytics strategies at WW. She excels at translating ambiguous business needs into actionable problems and identifying the right methodologies to address them. Her passion is helping WW employees use analytic results to drive decision making and improve the business. As a lifelong athlete she knows the dedication and strength it takes to complete any challenge. Agenda: - Pizza and socializing begins @ 6:45 - Talk begins @ 7:00 followed by Q&A - A little extra socializing after the event

Past events (58)

Why No One Is Looking at Your Data

work—bench

$10.00

Photos (126)