Machine Learning Demystified

    By: Michelle Hardwick on Mar 29, 2019

    Michelle Hardwick_Machine Learning.png

    A COLLABORATE 19 Session Preview with Michelle Hardwick

    Michelle Hardwick is the Director of Data Science and Analytics at Salt Lake Community College, serving in a non-teaching position that focuses on analyzing data to improve student success and help students at risk of dropping out. Michelle’s career has been focused on analytics, spanning a number of different industries. She began as a data engineer in healthcare, then moved to analytics in retail. From there, she was an analytics consultant for a number of other industries. Michelle notes she has “always been drawn to education and helping people learn and grow,” which is what brought her to the academic space.

    For the last six years, Michelle has also taught graduate-level analytics courses at Utah State University and the University of Utah. This month, Michelle will bring her teaching skills to a different kind of “classroom” at COLLABORATE 19, held in San Antonio, Texas, April 7-11.

    We caught up with Michelle to learn more about her COLLABORATE 19 presentation, “Machine Learning Demystified.”  

    Why are you presenting on this topic and what is its importance in the field?

    Machine learning—or, put simply, the process of finding patterns in data—is a hot topic that many people talk about, but even more people do not know much about and are curious about it. Machine learning can sound so intimidating because there are many algorithms and even vocabulary words that are new to those not in data science. There are also a bunch of tools out there that do some form of machine learning. I want to get people to the point where they can have intelligent conversations about the topic and maybe even take on a machine learning project of their own. I think this session will be helpful for DBAs who are looking to pivot within their career, or just want a better understanding of what their data and analytics teams are doing.

    What are three takeaways you hope attendees get from this session?  

    Attendees will understand more about how to approach a machine learning problem, and the steps to take. They’ll understand how to pick the algorithms that they want to run against their data for machine learning. Finally, they’ll get a look at the machine learning capabilities already built into SQL Developer so they can try out a machine learning problem on their own.

    Why are events like COLLABORATE important to the profession?

    When I attended my first COLLABORATE conference, I had major “imposter syndrome”: I thought everyone in the room would know so much more than me. I quickly realized everyone is trying to learn and you are not the only person in the room who’s new to a topic or trying to soak more in. Technology is changing so fast and it’s difficult to be an expert at every aspect of it.

    I also think that COLLABORATE is important for building a network of people who do similar things within the industry, or even in other industries. I didn’t realize so many of us are trying to solve similar problems and we can learn from each other’s experiences. I like that I can reach out to people I’ve met at COLLABORATE and ask how they are using a new feature of the database or what they did when they encountered a certain error. Everyone is so helpful!

    COLLABORATE takes place April 7-11, 2019, in San Antonio, Texas. Visit IOUG’s COLLABORATE website to register, take a quiz to find the sessions that best meet your needs, and more.

    Released: March 29, 2019, 8:34 am | Updated: April 10, 2019, 11:34 am
    Keywords: Feature | SELECT Journal | COLLABORATE 19 | machine learning | SELECT | SELECT Journal

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