Software I wrote
SimpleLearner: Implements an easy to tune polynomial deep learning network. Download from GitHub.
Scraping ArXiv: Script for scraping ArXiv meta data and doing some exploratory statistics of manuscript ArXiving. Download from github.
FPF R Package: Finds the prevalence of activation in fMRI group studies, presented in our paper.
Software I use
- Ubuntu- a friendly Linux distribution with Hebrew support.
- Version control: git with github for code, manuscripts, etc.
- Scribus- for scientific posters.
- Zotero- for managing references (I like Mendeley, but I am already addicted).
- Calibre for managing my (e)book library.
- Reeder- by far my favorite RSS reader (since GoogleReader closed).
- Pocket- For all the “I want to read this later” sites.
- Jekyll with GitHub: for blogging.
- Linux Shell and system administration:
Software I want to try but didn’t have the time yet:
Hardware I use
- Server- Lenovo X3750-M4: Just because I find that the batch cluster computing paradigm (e.g. Condor, SGE, etc.) is not suited for modern interactive data analysis. I found that you can get much more done with a single, massive, multiple core, RAM rich, server (running RStudio Server obviously).
- Laptop- Lenovo T460s: The size of the X1 with the power of the T series.
- Cloud- AWS: For any ad-hoc hardware needs (which is quite often for me), I just start an EC2 instance.