ChiPy Data Science SIG: April Meeting

First Data Science SIG of the year! We have two Data Scientists Mark Hoffmann and Zax Rosenberg talking about their projects.

Talk 1: Neural Networks for Multi Level Forecasting

Forecasting is a hard problem to do well. What happens when you are not only forecasting a single series, but you have to forecast tens of thousands of series simultaneously? This talk will cover some non parametric methodologies for working with this idea of many time series. We will go over basics of neural networks, entity embeddings for categorical features, competing methodologies, real world implementations that have attained state of the art results, and some common applications of these models such as anomaly detection.

About the Speaker:

Mark Hoffmann has been working on business and research endeavors related to technology for nearly a decade. These pursuits began at Augustana College where he worked in a research lab that focused on high energy nuclear physics as well as one that was focused on quantum optics. While in undergrad, he co-founded a software company called 38th Street Studios. Mark then ventured to Raleigh, North Carolina where he worked towards a masters in analytics from NC State's Institute for Advanced Analytics while working with a government agency on data science efforts related to network optimization and event sequencing.

Following development efforts of 38th's first major software platform, Mark moved back to Chicago to work full time on the startup, which later went on to act as a major transportation logistics system that has served executive travel for major events such as the 2018 Superbowl. Continuing to work towards a goal of democratizing technology, data, and automation in every day lives, he has helped lead efforts and develop software for clients of 38th Street Studios that continue to flourish with great people in domains that span logistics, construction, and real estate.

Mark has recently spent time in health insurance, where he has worked on teams to optimize provider networks as well as leading an initiative for a time series based anomaly detection framework.

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Talk 2: Association Rule Learning in Python

A rule based machine-learning(data mining) method for discovering interesting patterns between variables in large databases in a human-understandable way. He talks about two steps: Frequent Itemset Mining and Rule Generation. The talk will also have a real-world example to help us understand it better.

About the Speaker:

Zax Rosenberg is currently a Data Scientist at SPINS, where he develops data-driven analytic solutions for grocery retailers. In his “free time” he is the Senior Mentor for ChiPy‘s (Chicago Python User Group’s) mentorship program, as well as an avid tech enthusiast/blogger.

Prior to joining SPINS, Zax spent eight years in the finance industry, including nearly four years as an Equity Research Associate for Baird, covering public transportation and logistics companies; and four years in the single family office industry (most recently as a Senior Investment Analyst) sourcing, evaluating, selecting, and monitoring long only funds, hedge funds, private equity funds, and direct investments, across asset classes, as well as managing multi-billion dollar portfolios’ allocations and risk.

Zax also previously served as Chairman of the Board for the Dean’s Advisory Council for Roosevelt University’s Walter E. Heller College of Business Administration from 2012-2015, and is an established entrepreneur. Zax graduated with highest honors from Roosevelt University with a BS in finance, and is a Chartered Financial Analyst.

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So, what are you waiting for? RSVP now for great talks along with amazing refreshments on April 18th at Metis.