Hi there.
I am a PhD student and I am grateful to be working at the intersection of engineering, statistics, computer science, and machine learning.
In this blog, I will mainly share with you my enthusiasm for programming and algorithms.
I will be mindful that most of what we’ll be doing has a high carryover for your projects.
No explanations with oversimplified examples. No tutorials of stuff that hundreds of people have already explained much better than I ever could. Unfortunately, this also means that this blog is mainly aimed at advanced programmers.
Some items on my list are:
- Extending and improving SciPy’s FFT library.
- Writing a flexible and minimal-overhead FFT library binding that can be used in Numba just-in-time compiled code.
- Making Numba aware of
scipy.fft and numpy.fft.
- Learning how to write Python bindings for existing C/C++ libraries using C extensions, Cython, and Pybind11.
- Writing efficient algorithms beyond Big O, e.g. writing algorithms optimized for your hardware.
- Competing against the state-of-the-art algorithms implemented in major libraries such as SciPy or Scikit-Learn.
- Piquing your curiosity about Python by explaining fascinating, hardly documented or undocumented features and peculiarities.
Most of these codes exist already and are collecting dust on my hard drive. Now I want to share them with the open source community.
See you in the blog section!