• IoT and ML: third and final meetup

    United States

    *** PLEASE NOTE – IMPORTANT CONTENT *** This final meetup is no longer at the Carlson School at the UofM. It is now at Lab651: 550 Vandalia Street, Suite #224 Saint Paul, MN 55114. For details on how to navigate the building, please see the bottom of this page: https://lab651.com/contact/ If you have trouble finding the place, give me a call at four-oh-two two-1-six six-seven-oh-five ***** Also note that the building automatically locks doors to the outside at 7pm. We'll have someone stationed there until a few minutes after 7, but they'll need to leave shortly after in order to enjoy the rest of the meetup. So, please try your best to arrive *before* 7pm so you won't run the risk of being locked out. The actual meetup itself will last around an hour, and then we'll head over to Lake Monster Brewing (located in the same building) for a happy hour to celebrate the end of the project. ----- Final meetup for IoT and ML challenge In this meetup, the two teams (image recognition and autonomous vehicles) will present their work from the past few months!

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  • IoT and ML: second meetup

    University of Minnesota: Management Carlson School of

    Intermediary check-in event for IoT and ML project Please welcome special guest Michael Prom from Boston Scientific! (https://www.linkedin.com/in/michaelprom/) Learn about how Boston Scientific is revolutionizing the manufacturing of medical devices through the use of artificially intelligent devices (AIoT). From design and development of an autonomous image capture system to applying AI at the edge. Strides in technology are helping advancing science for life. Even if you are not in the medical device industry there are a lot of lessons to be learned that can be applied to your own industry or personal projects.

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  • Getting our hands dirty: the IoT and machine learning

    Herbert M. Hanson Jr. Hall

    StarEightyTwo is back! Join us near the end of this year for an introduction to a little bit different kind of challenge: data science and the Internet of Things. As tonight's speakers, we welcome Madhu Tennakoon and Dan McCreary. Madhu is a machine learning developer at 75F. Madhu participated in IoT Hackday a few weeks back, building in 12 hours an image recognition system which he then used to create an autonomous robot. Dan, a Distinguished Engineer at Optum, is heavily involved with STEM education through avenues like Coder Dojo and Arduino.MN. He does a lot of work building inexpensive Arduino kits with which kids can "get their feet wet." As mentioned, this challenge will be different from our usual engagements. This time, the project will revolve around learning about and (if you're already a bit knowledgable) flexing your muscles as it relates to hardware, software, and "cool" applications. Rough agenda, with things formally kicking off at 7:00pm (of course, feel free to show up a bit early to grab pizza and get settled so we can start promptly at 7): 1. Welcome and introduction to the hands-on project 2. What you can do with inexpensive Arduino kits – Dan (~30-45 minutes) 3. IoT Hackday project walkthrough, Madhu + Q&A (~30-45 minutes) 4. Begin brainstorming/researching your own projects, forming teams

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  • New Year's Data Science Resolution Grand Finale

    Herbert M. Hanson Jr. Hall

    Room 1-111 Join us for the grand finale! Each team (real estate, Avivo, and Science Museum) will have 30 minutes for presentation and Q&A of the work they completed over the last three months! More details to come...

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  • New Year's Data Science Resolution: predictive modeling tutorial and workshop #2

    Room 1-111 Similar to the first tutorial/workshop, we will go through two predictive modeling approaches, this time related exclusively to the real estate dataset. Kevin Church will present a multiple regression approach, and John Hogue will present an approach more up the machine learning alley.

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  • New Year's Data Science Resolution: data wrangling tutorial and workshop #1

    Room 1-111, Herbert Hanson Hall (not Carlson!) In the second episode of the New Year's Data Science Resolution, join us as we check in with each team, bounce questions off of each other, and go through a data wrangling workshop/tutorial related to one of the three selected projects! John Hogue will conduct the tutorial, in which he'll go through the steps of integrating third-party data and general data wrangling for the real estate predictive modeling project.

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  • StarEightyTwo & Social Data Science: a New Year's Data Science Resolution

    University of Minnesota: Management Carlson School of

    Room: Carlson L-114 StarEightyTwo and Social Data Science present: a New Year’s Data Science Resolution We invite you to hit the ground running in 2018 with a New Year’s Data Science Resolution! Remember all of those project ideas you hastily scribbled down in 2017 (or perhaps even earlier) but never got around to starting? Now’s the time to begin! This project will last from late January until mid-April, and will consist of five meetups: the kick-off, three check-ins/tutorials/workshops, and a grand finale. Here's what you need to know for the kick-off: First, we'll present the main project – a Data Science Resolution. Next (this is where you come in), attendees get the opportunity to pitch, in a shark-tank sort of way, their respective projects/ideas. These projects could range from ideas you thought of personally to projects for one of your favorite organizations (e.g. a non-profit – more details to come on how to approach and "pitch" our services to a potential partner). After the pitches, everyone will vote for the top three projects to pursue as a group over the next 3-4 months. Then, we'll have a matchmaking session in which individuals can join the team whose project most interests them. That's the core of this meetup – what follows will be explained in detail near the end of the evening. Please see the Slack group (join here if you haven't already (https://join.slack.com/t/stareightytwo/shared_invite/enQtMjgyOTcxNjM0MjI0LTM3YmFmYzRhZjA5YmJjMWZkNzY4M2ZmNDJkZjk3YTJiODAyZDAwMmNlYjhkMWU2MjMxYzkwMDExZDYxYThhMWQ)) for more information regarding what to cover during your pitch! Following these guidelines will help to ensure uniformity across pitches, which will allow the substance behind each project to shine! Also, if you plan to pitch an idea, please comment below so we have an idea of how many different presenters to expect for this meetup. To put it briefly, here's what we'll accomplish in this meetup: 1. What is a New Year's DS Resolution? 2. Pitch time! 3. Voting 4. Team matchmaking 5. Next steps See you all soon!

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  • Mapping Prejudice: an Interactive Look at Inter-rater Reliability

    University of Minnesota: Management Carlson School of

    Room: Carlson L-114 (located on the lower-level of the Carlson building) Please bring a laptop/tablet, if you have one! -------------------------- StarEightyTwo + Mapping Prejudice: an Interactive Look at Inter-rater Reliability Join us on Wednesday, November 15th for an engaging deep-dive into a topic most analysts/data folks don't encounter frequently in their day-to-day work: inter-rater reliability (https://en.wikipedia.org/wiki/Inter-rater_reliability)! For this event, we're partnering with Mapping Prejudice (https://www.mappingprejudice.org/), a project based out of the University of Minnesota devoted to identifying, indexing, and visualizing racial covenants (i.e. racial housing deed restrictions). Agenda: • 6:00-6:30 - Networking/general merriment • 6:30-6:40 - Welcome • 6:40-7:00 - Introduction to Mapping Prejudice (Kevin Ehrman-Solberg, MP) • 7:00-7:30 - Interactive rater reliability exercise • 7:30-8:00 - Introduction to rater reliability • 8:00-9:00 - Rater reliability and Mapping Prejudice work

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