First off, thanks for stopping by!
My goal for this site is to document my journey to becoming a machine learning practitioner. I was first exposed to Artificial Intelligence during my time at the University of Missouri in the late 80s. A good friend of mine talked about neural networks, supervised learning, and backpropagation. I have been intrigued every since.
A little about me
After I was done with school, I played around with the Stuttgart Neural Network Simulator, but never really went anywhere with it as many of the concepts were way over my head. I didn’t have a sufficient level of math experience to really wrap my head around it.
Through the years, I’ve dipped in here and there purely as a hobby to see where things stand. But, it was always slow and even more difficult to understand.
A few years ago, I found myself working for a software company that developed tools for the bioinformatics industry. A lot of their technology was based on high level statistics and probabilistic modelling. I worked with some very smart individuals.
Around the same time, machine learning was getting hot. I started paying attention to where things were going. I started working with Python also at the same time. Now, two jobs later I have managed to transform myself from a UNIX/Linux systems administrator to a Python engineer. I feel as though I am finally ready to get over the hurdle and move into machine learning as the next phase of my career.
Today, computing power is relatively inexpensive. I have a GPU in my personal workstation that is powerful enough to make projects not take the rest of my life to complete. And the tools have greatly reduced the amount of math needed to understand how to approach a problem.
That being said, I am sure that I will still need to learn a fair amount of math to get the job done. But, we can deal with that when we need to.
It seems like there is no end to suggestions from folks on how to go about learning this space. What this means for someone like me is “analysis paralysis!” I have looked at so many different options, afraid of picking the wrong path. I have spent countless hours reading blog posts, watching YouTube and generally procrastinating instead of starting.
So, here I am. I’m just going to start. I should know better that there isn’t one “right” way to go on this. Nothing in IT works like that. So, I’m just going to start.
I have a general curriculum that I plan to follow that doesn’t appear to involve any heavy math until the last two books. But, if it start to get deep, I have some options that will help pick up linear algebra and statistics when I need it.
The first book that I am planning to work through is An Introduction to Machine Learning with Python by Andreas C. Müller and Sarah Guido. It uses the scikit-learn library.
I have some thoughts on where to go next, but I don’t want to get ahead of myself.
I’ll be documenting my thought and observations as we go on this journey.
I welcome any feedback and suggestions along the way.
Thanks again for stopping by!