This is a page with a collection of links to materials that I have found helpful for scientific computing.
Document Processing
GUI editor for LaTex-style documents.
Never waste money on Microsoft products again.
Full-featured LaTex editor.
BibTex references manager.
Tricks:
Data Analysis in Python
Cheat Sheet (Data Structures, Numpy, Pandas)
The most user-friendly Python environment, includes almost all the packages you will need. I work in Spyder, although many people use PyCharm.
Statistics in IPython.
“Natural Language Processing with Python” book
Recommended Modules:
- pandas (data management)
- scikit-learn (machine learning)
- NLTK (natural language processing)
- gensim (topic modelling and word embeddings)
- tensorflow keras (neural nets)
- huggingface transformers (transformer models)
- statsmodels (statistics)
- selenium (web scraping)
Upgrading your code (Mauro Luzzatto)
Relational Databases
Connect to a Postgres server in Python.
Import SQL data as a pandas DataFrame.
Miscellaneous
FTP and SFTP access.
Synchronize files across machines.
The industry standard for version control.
Persistent SSH access with session multiplexing (see here and here).
PDF tool for batch split, merge, etc.
Batch image processing.
Open-source video player. OpenSUSE Media Codecs.
Running Linux programs on Windows:
- Stop procrastinating and change to Linux
- Gow (GNU on Windows).
- Cygwin (cheat sheet)
Music
- The best, easiest, open-source, platform-independent audio recording application.
- Open-source digital audio workstation (a steep learning curve!).