Tag Archives: ML

ITKAN October 2021 Meeting | Machine Learning by Example | A night time city scape overlaid by blue light streaks | The ITKAN circuit tree logo in the lower left

October 2021 Meeting – Machine Learning by Example, Reprise

Register for the October 14 meeting.

Join us as SPR’s Chief Architect, Pat Ryan, reprises his February presentation on the topic of Machine Learning. He’ll show some interactive examples of how to apply it while he explains the what’s and why’s of the technology. No programming skills are required.

After a general overview, Pat will cover the following topics:

  • Autonomous driving
  • A “The Titanic” survival simulation
  • Image categorization
  • Facial recognition
  • Pose detection (*New Addition*)

DATE AND TIME
Thu, October 14, 2021
5:30 PM – 7:00 PM CDT

LOCATION
On-line

Pat Ryan: Pat Ryan likes to work on problems that matter. He applies software tools and techniques to the problems we have around us, with the goal of making the world a better place because of it. At SPR, Pat works closely with clients to understand their needs and craft solutions to help make them more successful. He also work directly with various engineering talents to pull together highly functioning teams. Pat is a player-manager. That means, he stays current with as many technologies as possible so he can understand and empathize when a team is struggling, and help them at a very concrete level. Pat continually builds his knowledge by reading technical books, attending classes, and coding something every day. Pat’s career has seen it all – from managing teams, to building a company from the ground up, to dreaming up software and devices that have gone on to solve client problems.

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ITKAN June 2021 Meeting | Meet CARBY | A hand holds a smart phone with the Carby app loading while a glass of iced coffee rests on a coaster

June 2021 Meeting – Carbon Footprint Digital Assistant – Carby

Register for the June 10 meeting.

Join us as ITKAN continues its journey on artificial intelligence, machine learning, and data science with a presentation by data science / machine learning award-winning practitioner Kevin Hartman. He will discuss and demonstrate Carby, an app that provides consumers quick access to information about the products we choose related to their impact on our environment simply by snapping a photo! Using the power of Ai, Carby will reveal the product’s carbon score and suggest lower impact alternatives if they exist.

The team that Kevin is part of recently won the World Innovation Day Hackathon, an international competition to demonstrate the creative use of technology to address our global challenges in achieving a more sustainable future. See the app and learn how the team plans to build Carby into a production-capable system that includes more Ai models and an automated data pipeline.

DATE AND TIME
Thu, June 10, 2021
5:30 PM – 7:00 PM CDT

LOCATION
On-line

Kevin Hartman is a fastidious problem solver, an expressive communicator, and a career learner. He loves solving complex problems using technology and data, turning the result into something simple and effortless. His specialty is formulating high-impact solutions that leverage technology innovation. From this passion he became versed in the skills of Product Management, Software Engineering and Data Science, and has education in all three. He has inspired, influenced, and led the creation of hundreds of digital products; working from both inside and alongside teams of researchers, scientists, designers, engineers and enthusiasts.

ITKAN February 2021 Meeting | Machine Learning by Example | A night time city scape overlaid by blue light streaks | The ITKAN circuit tree logo in the lower left

February 2021 Meeting – Machine Learning by Example

Register for the February 11 meeting.

Join us as ITKAN kicks off the new year with a presentation by SPR’s Chief Architect, Pat Ryan. He will introduce the topic of Machine Learning and show some interactive examples of how to apply it. No programming skills are required.

  • General Overview
  • Autonomous driving with an 8-bit simulation of a car driving on a track. Imagine… Pong meets Tesla
  • Can we use data from the Titanic to predict if Jack or Rose would survive?
  • Using Machine Learning to categorize images. Can we train a model to tell the difference between a picture of a highway and a beach? Can we train a model to classify pictures of cats and dogs? What happens if we try to classify a highway picture for the Animals model? We will look at 2 data sets:
    1. Scenes from highway, forest, ocean dataset
    2. Animals from Cat, Dog, Pandas dataset
  • Use reinforcement learning to teach a system to find the winning square while avoiding the losing square. As the system plays the game, it starts to learn what moves will bring positive rewards and what moves will bring negative rewards. In the end the system almost never loses!
  • Facial recognition is a very controversial topic and technology. But how does it work? We will look the basic algorithm behind facial recognition to gain a better understanding of some of the details.

DATE AND TIME
Thu, February 11, 2021
5:30 PM – 7:00 PM CDT

LOCATION
On-line

Pat Ryan: Pat Ryan likes to work on problems that matter. He applies software tools and techniques to the problems we have around us, with the goal of making the world a better place because of it. At SPR, Pat works closely with clients to understand their needs and craft solutions to help make them more successful. He also work directly with various engineering talents to pull together highly functioning teams. Pat is a player-manager. That means, he stays current with as many technologies as possible so he can understand and empathize when a team is struggling, and help them at a very concrete level. Pat continually builds his knowledge by reading technical books, attending classes, and coding something every day. Pat’s career has seen it all – from managing teams, to building a company from the ground up, to dreaming up software and devices that have gone on to solve client problems.