There and Back Again

This is it. One year ago tomorrow, I started writing this blog. I can't believe I made it a full year, writing an entry every single day. I remember celebrating making it a month, and celebrating making it 100 days, but a whole year? I'm glad I did it, and I think it served great purposes. Some days were harder than others. Some days, it was the last thing I wanted to do, but I got it done anyways. There were a couple in there where I fell asleep studying, woke back up and wrote my blog entry half asleep. Some of them are pretty rough when I read back through them, but there are some real gems in there as well. The main point, though, is that I stuck with it, and that's important to me. For the most, I really enjoyed writing it, and it got a lot of my thoughts out on paper. Whenever I was struggling with something, it always helped me to write about it. I always felt a little better after that. If anyone is considering writing a blog to document their progress, I would highly recommend it. I think it's a great way to represent your journey and it's therapeutic in its own way.

Anyways, on to the code. For nearly a month now, I've been learning all about the world of Python, specifically Data Science and Machine Learning. This, in and of itself, is a massive amount of material to take in. Jumping from JavaScript to Python has been really smooth; other than some syntax changes and a few rules changes, it's been a pretty simple transition. Learning Data Science and Machine Learning, however, is a beast. There is a lot I need to refresh myself in the world of Statistics, and possibly Calculus a little further down the road, so I've started taking a crash course on Statistics as well. Overall, though, the concepts make a lot of sense to me. I think with some serious practice, I can get really good in this area. I would say, to get to where I need to be with it, it will probably take a really dedicated year's worth of studying, but I know I can do it. Just like I was when I started learning web development, I'm highly motivated and really enjoy the material. It's a lot of fun to work with, and I get to make some awesome graphs along the way.

To learn this material, I started with Andrei Neagoie's course on Python. I've taken several courses by him in the past, and his pace is perfect to start with. He goes very slowly and tends to explain it on a level a 5 year old could understand. If I learned from another course and then came back to his course afterwards, I probably would have been bored out of my mind, but to start off with that was perfect. As a follow up, he had another course strictly on Machine Learning and Data Science, which was perfect. In one of the last sections of his Python course, he introduced these concepts and it really piqued my interest. I had always been familiar with the topics, and they'd been on my radar for a while, but this really got me going. Using packages like Pandas to create dataframes, Matplotlib to make really cool graphs, and Scikit-Learn to build models was awesome. It seemed like it was going to be a lot of work, but I think it will really pay off. I think we're in a similar position with Machine Learning as web development was around 2000. Everything blew up fast, and there were jobs all over the place. Every company is going to have a Data Science team here pretty soon, and it's only going to keep growing from there.

Until tomorrow!