GraphLab NY Users Meetup

News (oct 12): NY Machine learning meetup have kindly agreed to host our meetup on their list (https://www.meetup.com/NYC-Machine-Learning/events/212986652/). Thanks again to Paul Dix (http://www.linkedin.com/in/pauldix) for making this happen.

Join us for a social gathering at Knewton HQ in NYC.
There will be hands-on data science with lectures from Knewton and GraphLab, mingling and snacks.

6:30: Registration

7:00 George Davis, Head of Data Science, Knewton: Scaling Adaptive Education

Abstract - In the thirty years since Bloom attributed a 2-sigma improvement in educational outcomes to tutoring, differentiated learning has remained difficult to deliver at a reasonable cost to a mass audience. I will present Knewton's approach to this challenge, which focuses on scaling both user and content pools to achieve a better understanding of each. The talk is organized around three challenge problems relating to online modeling of student proficiencies, identification of multi-concept dependencies for assessments, and human-assisted inference of a latent matrix of content relationships.

George B. Davis, PhD - As Knewton's Head of Adaptive Learning, George oversees a team of engineers and data scientists implementing a realtime modeling, analytics, and recommendation infrastructure designed to route students more rapidly through educational content. George received his B.S. and PhD from Carnegie Mellon University's School of Computer Science, where his research focused on applications of probabilistic graphical models to supervised and unsupervised problems involving temporal, relational, and geospatial data.

Knewton (http://knewton.com) - Knewton is an education technology company that personalizes digital courses so that every student is engaged and no one slips through the cracks. As students progress through a Knewton-powered course, Knewton figures out what each student knows and how that student learns best, then recommends what to study next. Teachers use Knewton-powered predictive analytics to detect gaps in knowledge and differentiate instruction for each student. With approximately 7M students actively using Knewton in for-credit courses, we have one of the largest and richest data streams dedicated to learning, and are using it to learn more about how adaptivity can assist every student.

7:30: Rajat Arya, GraphLab: Building data products with GraphLab

What is a data product, and why should I be thinking about them? Rajat Arya will walk through examples of data-driven products, why we should focus on building them, and some how-tos and best practices for building one.

About GraphLab (http://graphlab.com/):

GraphLab is creating the software platform that lets data science teams---regardless of size or industry---get big data insights fast. To get value from their big data, organizations today require the deep expertise of data scientists and a large engineering team to integrate a range of complex tools. GraphLab’s flagship product, GraphLab Create, greatly simplifies big data analysis by combining all phases of the prototype-to-production process, allowing a single data scientist to do the job of many.

View our latest GraphLab Conference Keynote:

https://www.youtube.com/playlist?list=PLRu6_g339G-f-UuGxxPRzJeYHN6lItKCK

About Rajat

Rajat is a software engineer with over a decade of commercial industry experience. Most recently he spent three years in the AWS Database Services group focusing on building fault-tolerant high-performance distributed systems. He is a part-time graduate student studying Computer Science at University of Washington, and holds a bachelors degree in Computer Science from University of Pennsylvania.