Search Results for "dig"

Spyder is a free and open source scientific environment written in Python, for Python, and designed by and for scientists, engineers and data analysts. It features a unique combination of the advanced editing, analysis, debugging, and profiling functionality of a comprehensive development tool with the data exploration, interactive execution, deep inspection, and beautiful visualization capabilities of a scientific package. Spyder’s multi-language Editor integrates a number of powerful tools...

...The curriculum demystifies tools like bash, vim, git, and make, showing how to combine them into efficient workflows that scale from homework to production systems. Lessons dig into practical topics such as environment management, job control, shell pipelines, profiling, and reproducibility, with an emphasis on habits that save time and prevent errors. The materials are designed to be approachable for beginners yet still valuable to advanced users who want to sharpen their tooling. By the end, learners can work faster and more reliably because they understand the mechanics of their everyday tools.

...Instead of simply translating a query into keywords and returning a flat list of matching papers, PaSa uses a dual-agent architecture (Crawler + Selector) that can iteratively search, read, analyze, and filter academic publications — simulating how a researcher might dig through citation networks, expand references, and evaluate relevance based on both metadata and content. Given a complex scholarly question (for example, “Which works focus on non-stationary reinforcement learning with UCB-based value methods?”), PaSa decomposes the task: the Crawler generates search queries, retrieves candidate papers (via search tools and citation expansion), then adds them to a “paper queue.” ...

The key difference with current graph deep learning libraries, such as PyTorch Geometric (PyG) and Deep Graph Library (DGL), is that, while PyG and DGL support basic graph deep learning operations, DIG provides a unified testbed for higher level, research-oriented graph deep learning tasks, such as graph generation, self-supervised learning, explainability, 3D graphs, and graph out-of-distribution. If you are working or plan to work on research in graph deep learning, DIG enables you to develop your own methods within our extensible framework, and compare with current baseline methods using common datasets and evaluation metrics without extra efforts. ...

...Since it simplifies things DDS is not usable for all kinds of scrapers, but it is well suited for the relatively common case of regularly scraping a website with a list of updated items (e.g. news, events, etc.) and then dig into the detail page to scrape some more infos for each item. Django Dynamic Scraper tries to keep its data structure in the database as separated as possible from the models in your app, so it comes with its own Django model classes for defining scrapers, runtime information related to your scraper runs and classes.

Our premise when starting this project was that why do we have to dig through arrays of normative values to find the group our patient belongs to. Then proceed to manually calculate its z score and find out where it is on the percentile graph, when we could have a software that could do it for us. We weren’t able to find one in the literature. Thus came the PsiNorm. Currently only a demo for english exists, while Turkish adapted version is fully functional.

...The main goal of this project is to create an SSD implementation that is well documented for those who are interested in a low-level understanding of the model. The provided tutorials, documentation and detailed comments hopefully make it a bit easier to dig into the code and adapt or build upon the model than with most other implementations out there (Keras or otherwise) that provide little to no documentation and comments. Use one of the provided trained models for transfer learning.

digSetStat helps tracks volleyball stats (serving, hitting, blocking, defending, serve receive) during a match. It facilitates the job of the stat-taker by providing them with photos of the relevant players in the correct layout.

The Wion Result Viewer is a python plugin for Quantum GIS. It is used to load and view the result of Dutch dig alerts, made according the law WION, into Quantum GIS. It is an alternative to the free Klic-viewer provided by Kadaster.