The purpose of the this blog is to document my journey in learning the Julia programming language. As a previous MATLAB and Python / numpy user for many years, I am interested in bringing the best of the Julia language into my work.

I am a computer vision research scientist. I use Python and Jupyter notebooks daily in my research, and am looking for a way to multiply my effectiveness. In the image processing and computer vision domain, I am constantly frustrated by having to remember that my images are “RGB” rather than “BGR”, and that x- and y- indices in images are constantly backwards. But that’s just one small piece - in addition to fixing annoying peeves with the language and conventions, Julia is also blazing fast, almost as fast as C in some cases. Using the same code for prototyping and “production” (whatever that might mean in your context) sounds very appealing.

Friends have been encouraging me to learn Julia to fix some of my biggest woes with Python and numpy and beyond. To avoid procrastinating on learning Julia, I decided to make this blog to document and share my experience. It will provide motivation for me to learn and hack around with Julia, documenting my entire progress.

If you have any ideas for projects for me to do, libraries for me to look at, or interesting content you want to see on this site, feel free to send me an email or reach out to me on Twitter. I also do lots of things outside of computer vision, you can read more about me on my personal blog.

If you want to follow along, you can:

  1. Add Learning Julia directly to your Feedly
  2. Or your favorite RSS reader
  3. Follow @learningjulia on Twitter

The best is to add the RSS feed to your favorite blog aggregator, because I often forget to post on Twitter.