Search Results for ".lab"

Growth Lab is an open-source agentic growth workspace that connects product understanding, market research, execution, measurement, and iteration. It uses Codex or Claude Code as the runtime and treats natural-language conversations as the control surface. Collectors gather product, market, content, and channel evidence, while executor skills help create, publish, review, and coordinate growth work.

Python course (in Spanish) for Proteomics analysis using basically Jupyter NoteBooks. For more information, you can have a look at the readme.md file in the source code tree: https://sourceforge.net/p/lp-csic-uab/p4p/code/ci/default/tree/readme.md

...was conceived in 2010 as a way to reduce the workload of an over-worked professor teaching a CS data structures class. It proved not only to reduce the grading workload, but also improved the lab completion rates among students, and grades overall improved as a result. Since it has turned out to be such a successful tool, it is now released under the AGPL license for others to use in their classrooms. Planned improvements include: automatic plagiarism detection, making the student interface prettier, and supporting other testing frameworks and languages.

ByoDyn (http://cbbl.imim.es/ByoDyn) is a software tool for the study of biochemical networks within the framework of systems biology. SBML compatible, ByoDyn is a group effort of the Computational Biochemistry and Biophysics Lab.

The Infoscape Research Lab hosts research projects that focus on the cultural impact of digital code. The lab engages in software and other new media tool development, code mapping, interface design, and new media content analysis.

Mind this project is no longer maintained. You might be interested in having a look at http://pythonhosted.org/plasduino/ instead. Framework for data acquisition through the parallel port, suitable for performing simple didactic physics experiment.

GuerillaTactics is an effort to bring "Computer Education Through Security Analysis". We aim to create a security education "lab kit" including management software and a curriculum framework.

Net.py is a tool for learning about neural nets. Currently, it only allows the user to experiment with a Hopfield net. I am now extending it to cover the Kohonen net. I'd be pleased to receive suggestions and criticism.