My team has made great progress on our project, AI for election predictions. We have gotten all of the data we need into our cloud provider, where we can now run queries against the data. Basically the point of our project is to use Oregon election data in order to make connections on why certain election outcomes happened.
The biggest roadblock so far is actually learning some statistics related concepts. Statistics and further data-science is pretty integral to our project goals and being effective. In a sense, we have been reverse engineering data science, and identifying knowledge gaps that we have so that we can fill in the missing pieces.
I think that this has made me realize that I really enjoy data science, and want to continue learning more about it. There are a lot of things I need to learn yet in order to build a good foundational understanding of data science. I am super looking forward to learning more and deep diving into it!
I had been told many times that to do data science, statistics is most important, as it introduces ways to think about data and number, as well as fundamentally important things to consider when trying to manipulate data. It’s also important to consider these concepts when you are thinking about how valid your output will be, or what you want the end result to look like.
I am also looking forward to seeing my teams progress as we start to get our master datasets together and looking to get it running against a machine learning model!
-Mitch
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