This month we are sponsored by Clarity Insights! (http://www.clarityinsights.com/)

When: Oct. 12, 2017, 6 p.m.

Where: University Center

Directions:

in the Lake Room

525 S State St, Chicago, IL 60605
in the Lake Room

Topics


  • Full Stack Python for AI: How open source Python enables each phase of the AI workflow
    (0:30:00 Minutes)
    By: Tripp Smith
    Experience Level: Intermediate
    Investments in AI are heating up, with the total market estimated as high as $126B by 2025. This talk will present case studies and code samples of how our clients are using Python today and how we expect this to evolve over the next few years as AI becomes increasingly ubiquitous. Python enables each phase of the AI pipeline: DevOps, Data Engineering, Model Development, Deep Learning, Cognitive User Interfaces, and Microservices. This talk will highlight how Python is a common glue across multiple disciplines that will allow cross functional teams work together to get real results from AI.
  • PyWeek 24 and pygames
    (0:10:00 Minutes)
    By: Michael Tamillow
    Experience Level: Intermediate
    Pyweek 24 is coming up October 15th through October 22nd! For pyweek 23, I created a game called the evolution of evil, which is available on my github repository. I will (very quickly) walk through the steps of how I created the game, and what it is.
  • Data Science Workflows using Docker Containers
    (0:30:00 Minutes)
    By: Aly Sivji
    Experience Level: Intermediate
    Containerization technologies such as Docker enable software to run across various computing environments. Data Science requires auditable workflows where we can easily share and reproduce results. Docker is a useful tool that we can use to package libraries, code, and data into a single image. This talk will cover the basics of Docker; discuss how containers fit into Data Science workflows; and provide a quick-start guide that can be used as a template to create a shareable Docker image! Learn how to leverage the power of Docker without having to worry about the underlying details of the technology. Although this session is geared towards data scientists, the underlying concepts have many use cases (come find me after to discuss).