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# This is a Markdown file for the GitBasic Demo

Test file

## This is a markdown file for Jared

I've been listening to a book about baseball. One of the chapters talked about why rookie playing cards were so important. "It's kind of like hitting the lottery, because we don't know who is and isn't going to be a hall of famer." It made me realize we can measure what makes a hall of fame player for each position and then use machine learning to predict a hall of fame player.

So I'm working on getting all of the data and then I'm going to build a NN to figure out a moving window of what a HOF(Hall of Fame) player. I could see this process being used for tallent aquisition as well...As long as we can measure what makes an employee a good employee based on metrics then we can determine who will be HOF workers(I hypotheses).