Purpose Of This Blog
Ever since my PhD I've been interested in machine learning, but I used to think it was too hard for someone without any programming background. Since I didn't see any direct use for ML in my research projects I couldn't justify learning about it at work, and I didn't have/take the time to do it at home either.
About two years ago something changed. I'm not exactly sure what caused it, but I decided to learn to code. I found a fantastic website called 'freeCodeCamp.org' and proceeded to blast through the exercises and modules until about halfway through the back end development certification part. By now I had done tons of javascript algorithm exercises and created a bunch of projects (hosted on https://codepen.io/chrisdinant/) and a few small websites.
Simon Game
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One of the projects of the freeCodeCamp front end curriculum
By now my scientific research had moved more into high-throughput automated microscopy techniques which create large amounts of data, meaning that I would have a use for ML tools at work.
So I stopped my web development training and focused on learning R and Python. Over the last year or so I have become a data science addict. I read everything I can find on anything related to data science. I take online courses on data science topics. I do Kaggle challenges. I train models on my microscopy data.
I have always known that my real passion was not science itself, or music or something else.
My passion is learning.
And I have come to the conclusion that for someone who loves analising data and learning new things all the time, DataScience is the ultimate profession.
That's why I have set my mind on becoming a data scientist.
On this blog I will post some of the things that I learn or have learned on the way to hopefully be of use to other people who are just starting to study DataScience.
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