About this blog

Since 2007 when I first started working with Python for my MSc. project, I’ve seen this language mature and flourish beyond my wildest dreams. In the past couple years, I’ve seen MATLAB fanatics making the switch, web-devs ditching PHP, and the hardcore C++ devs grudgingly admitting that maybe, just maybe, Python allows for more productive coding. And I couldn’t be happier!

This blog is dedicated to “the usage of the Python programming language in scientific endeavors”. A small subset of my posts will comprise opinionated dribble reflecting my humble opinion on different aspects of the Python, e.g. distributions, certain packages, etc. However, the primary purpose of this blog is to provide Python tutorials and promote time-saving yet little-known tools. Topics will include visualization, image processing, data analysis, high-performance computing etc etc.

All the material, i.e., the Markdown documents I wrote with Byword and published here, the IPython Notebooks with the code I’m presenting, and any supplementary data, can be found in the BitBucket repo dedicated to this blog.

So, welcome, do take a look around, feel free to drop me a line or comment, and I hope that you will gain something from this 🙂

Cheers from the land down under,
Adam

12 thoughts on “About this blog”

Nice blog! Thanks!

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somada141 on February 6, 2015 at 12:21 pm said:

Thank you Helder! Appreciate the thumbs-up 😀

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Your blog is amazingly useful dude, cheers!

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somada141 on December 18, 2015 at 9:55 am said:

Thanks mate, glad you found it helpful 🙂

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Thanks, your blog gives me a lot of help.

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somada141 on December 1, 2016 at 5:40 am said:

Glad to hear it Fabien 🙂

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What a wonderful blog this is!!
Thank you so much for helping me. T.T

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somada141 on March 22, 2017 at 8:24 pm said:

Thank you!!! 🙂

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Hi Adam,
Thanks for creating such a great blog . Your explanations for using VTK, SimpleITK, and Python in general are superb. I am especially interested in segmentation for radiation therapy purposes.
Do you know of any good resources for applying machine/deep learning algorithms to medical image segmentation? (By “good” I mean anything remotely similar to your blog/explanations.)
Thanks again,
Rob

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somada141 on October 2, 2017 at 5:53 am said:

Hi Rob and thanks a lot for the kind words. When it comes to applying ML/DL to medical image segmentation I’ve primarily come across interesting papers and a couple blog posts but I dunno if I’d call them detailed enough for my liking. An example would be:

https://blog.altoros.com/experimenting-with-deep-neural-networks-for-x-ray-image-segmentation.html

while I’ve come across this project as well but haven’t tested it:

https://github.com/DLTK/DLTK

All in all I’d start with the papers cause they provide more in depth info on the methodology.

If you’re keen to disseminate the topic and write a post on PyScience I’d love to give you author access so let me know 🙂

Cheers,
Adam

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