What we're about

This is a group for people enthusiastic about the application of data science, data visualization, data analysis, data systems and associated topics for learning and public benefit in Springfield Missouri, USA.

Purpose: meeting interesting people doing interesting things with data, learning from each other, supporting each other, community (pooling resources to achieve advantages), having fun, networking, and professional development.

We're actively looking for presenters and sponsors. If you're able to help out, let us know!

Presenter Application (https://forms.gle/9CPjCgQ27K3PbdBN9)

Sponsor Application (https://forms.gle/MWRKE5DHsBGXouBb7)

Big picture objectives:

1.) get a group of people working together to make Springfield a vibrant globally competitive community for people to learn data science, establish a career in data science, and create products and services that have a differentiating advantage rooted in sophisticated application of data science to important tenacious problems.

2.) leverage the substantial collective resources of teamwork to produce real working examples of data science for public benefit in Springfield, Missouri. We will work with government agencies, non-profit community groups and businesses within our gravity to generate projects that have public benefit, which enthusiastic technical segments of the group will volunteer to work on after their day jobs. These groups will then report back on their findings to the larger group and to community stakeholders.

While we expect the group whole to have a deep and broad spectrum of skills in technology, you do not have to be a techie to be in this group. All meetings will have a balance and given the time we have in meetings we will press speakers to describe the salient high level story in general meetings (the problem, the solution, and the resolution) as opposed to leading purely technical discussions. We will facilitate orbiting groups of people that have interest in joining together for detailed learning on new technical paths. The monthly general meetings will simply serve as a launching off and landing point for these journeys.

At our monthly meetings food, drink and interesting people doing interesting things will be provided. There will also be opportunity to join a deep learning subgroup (TBD) or show off your skills in a data science for good project (TBD) but if you just want to come to the monthly meetings that is fine too. Large group meetings are the third Tuesday of every month, 5:30-7:00pm. All are welcome.

Let me know if you are interested in co-leading, giving a presentation, leading a talk, leading a data science for good project, sponsoring this group, or otherwise shaping the group in ways that I have not imagined.

P.S. If you think the concept of this group is good please share with others you know. All are welcome. We are just looking for an enthusiasm about data science for collective learning and social benefit (to create better communities, better organizations, better people and a better world).

Upcoming events (2)

Utility Analytics and Azure Data Solutions: Data Science After Dark Feb 2020

This month we have two out-of-town guest presenters from The Energy Authority (TEA). TEA provides public power utilities with access to advanced resources and technology systems so they can respond competitively in the changing energy markets. http://www3.teainc.org/about-tea/ Details: We’ll be meeting at The eFactory (405 N. Jefferson Ave.) on Tuesday February 18th from 5:30p to 7:00p. We'll be in the BKD room (Enter front doors, first room on left.) Food and drink will be provided while everyone settles in. Please RSVP on meetup.com now so we can plan enough food and drinks. Agenda: 5:30-6:00 – Arrival, Food, Drinks, Networking 6:00-7:00 – Speaker Presentations Topic 1: Introduction to Quirkiness of Utility Analytics A few fun facts: (1) Wholesale energy price can spike up from median price of $30/MWh to $1000/MWh in a couple of hours or drop down to negative prices. (2) Market design can change behavior of market participants and thus the market itself. (3) “Data scientists” in utilities often do everything from data mining, model prototyping to production model engineering and support. There is so much analytics to be done with utility data. I’ll share a map of utility analytics and a few use cases. Presenter: Eina Ooka Eina Ooka is a senior quantitative analyst at the Energy Authority. She develops multivariate stochastic forecasting models for electric power markets and utility portfolios, utilizing both statistical and data science methods. She develops production-level models in R, all the way from R&D to the shiny app deployment that can be utilized throughout the company for portfolio management. Topic 2: Azure Cloud Architecture for Data Workloads Cloud solutions from AWS and Azure offer the ability to quickly standup environments that scale as you grow your solution. In this presentation, we'll provide an overview of the Microsoft Azure architecture we are using at The Energy Authority to process Smart Meter data and apply Data Science services across large datasets. We'll provide some lessons learned from real world development using Azure Data Lake, Azure Data Factory, Azure SQL, and Azure Data Bricks. Presenter: Brad Gall Brad Gall is a Cloud Data Architect with over 20 years' experience in Information Technology and Data Analytics. Working primarily with Microsoft data platforms, Brad has successfully delivered data driven projects across multiple industries in both corporate and consulting roles. In his current role as Senior Data Analyst with The Energy Authority, Brad works on the Connected Analytics team to help utilities leverage value from the increasing amount of data pouring in from big data programs such as Smart Meters. Resources: eFactory Parking: https://efactory.missouristate.edu/wp-content/uploads/2018/10/efactory_Event-Parking.pdf Meetup page: https://www.meetup.com/Data-Science-After-Dark/ Facebook: https://www.facebook.com/groups/475003726608912/ Slack: https://join.slack.com/t/datascienceafterdark/shared_invite/enQtNjg1NzkyNjQ4NDM5LTg4NjVmMGU3NzNjZDQzODc1YTYzMGQ0NGI2MzkyOGIxMjBkNzIyMjU5OWRjMTUxNzRmNDJlZDNkNzQzOGYwNmI

Attacking a Machine Learning Model - Data Science After Dark April 2020

Attacking a Machine Learning Model - Why we must protect ML models critical to our business: Machine learning models are designed to analyze input data and provide desired output data. What if we can manipulate the output data? I will demonstrate how easily we can attack an image classification model. We will feed an image of a specific animal into the image classification model and demonstrate how we can modify a single pixel in the original image to convince the model that the image is a different specific/desired animal. If you train any type of model for your organization, be aware that similar techniques can be used to bypass your model if an attacker can directly access your model. For example, an attacker could feed a fraudulent transaction into a fraud detection model and determine what transaction detail can be changed to fool the model into believing the transaction is NOT fraudulent. Details: We’ll be meeting at The eFactory (405 N. Jefferson Ave.) on Tuesday November 19th from 5:30p to 7:00p. We'll be in the BKD room (Enter front doors, first room on left.) Food and drink will be provided while everyone settles in. RSVP on meetup.com now so we can plan food, drinks, and meeting space Agenda: 5:30-6:00 – Arrival, Food, Drinks, Networking 6:00-7:00 – Presentation About Our Presenter: Jason Klein has been working with data for 15+ years. He takes a special interest in data analysis and machine learning in his role with an online restaurant reporting platform. Find slides for this talk, as well as recordings and slides for his past talks on his Talks page (https://jrklein.com/talks). Resources: eFactory Parking: https://efactory.missouristate.edu/wp-content/uploads/2018/10/efactory_Event-Parking.pdf Meetup page: https://www.meetup.com/Data-Science-After-Dark/ Facebook: https://www.facebook.com/groups/475003726608912/ Slack: https://join.slack.com/t/datascienceafterdark/shared_invite/enQtNjg1NzkyNjQ4NDM5LTg4NjVmMGU3NzNjZDQzODc1YTYzMGQ0NGI2MzkyOGIxMjBkNzIyMjU5OWRjMTUxNzRmNDJlZDNkNzQzOGYwNmI

Past events (5)

Data Science After Dark - December Social

Missouri Spirits

Photos (7)