Search Results for "hpc code analysis"

...It supports both GitHub URL crawling and local directory analysis, and can tailor output tutorials to different languages, making it accessible for international developers.

ThinkStats2 is the code and text companion for the second edition of Think Stats, an introduction to statistics and data science for Python programmers. It teaches probability and statistical reasoning through short programs, experiments, and analysis of real datasets. The material emphasizes exploratory methods that help readers ask and answer practical questions with data.

AutoResearchClaw is an open-source framework designed to automatically generate full academic research papers from a single idea or topic. Built in Python, it orchestrates a multi-stage research pipeline that gathers literature, formulates hypotheses, runs experiments, analyzes results, and writes the final paper. The system retrieves real academic references from sources such as arXiv and Semantic Scholar to ensure credible citations. It can automatically generate code for experiments, run...

The data-science-on-gcp repository is a comprehensive collection of code examples and end-to-end workflows that accompany the book Data Science on the Google Cloud Platform, designed to teach developers how to build scalable data science and machine learning systems using Google Cloud services. It provides structured, chapter-aligned implementations that guide users through the full lifecycle of a data science project, including data ingestion, storage, processing, analysis, model training, and deployment. ...

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

...Because it is code-first, users can copy, modify, and run the examples on their own datasets, encouraging experimentation and deepening understanding.

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.

This is a implementation of the 'enhanced Topic-based Vector Space Model' (eTVSM) using the python language. A Java-Version and maybe other java-code contributions are planned.