Search Results for "git:/git.code.sf.net/p/docfetcher/code" - Page 9
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Showing 763 open source projects for "git:/git.code.sf.net/p/docfetcher/code"
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Network Management Software and Tools for Businesses and Organizations | Auvik NetworksReduce IT headaches and save time with a proven solution for automated network discovery, documentation, and performance monitoring. Choose Auvik because you'll see value in minutes, and stay with us to improve your IT for years to come.
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The full-stack observability platform that protects your dataLayer, tags and conversion dataCode-Cube.io detects issues instantly, alerts you in real time and helps you resolve them fast. No manual QA. No unreliable data. Just data you can trust and act on.
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Lucid
A collection of infrastructure and tools for research
Lucid is a collection of infrastructure and tools for research in neural network interpretability. Lucid is research code, not production code. We provide no guarantee it will work for your use case. Lucid is maintained by volunteers who are unable to provide significant technical support. Start visualizing neural networks with no setup. The following notebooks run right from your browser, thanks to Collaboratory. It's a Jupyter notebook environment that requires no setup to use and runs entirely in the cloud. ... -
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ML for Trading
Code for machine learning for algorithmic trading, 2nd edition
On over 800 pages, this revised and expanded 2nd edition demonstrates how ML can add value to algorithmic trading through a broad range of applications. Organized in four parts and 24 chapters, it covers the end-to-end workflow from data sourcing and model development to strategy backtesting and evaluation. Covers key aspects of data sourcing, financial feature engineering, and portfolio management. The design and evaluation of long-short strategies based on a broad range of ML algorithms,... -
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SLAMBook-en
The English version of 14 lectures on visual SLAM
...The material covers both foundational theory—geometry, camera models, feature matching, pose estimation—and practical systems components such as optimization, map representation, loop closure, and real-time factors. It aims to bridge academic rigor with hands-on implementation: readers are encouraged to implement algorithms, read code, and follow along with the mathematical derivations and system design decisions. -
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HamsterLab
education, children, course, C programming language, maze, 2d graphic
...By now, please read the README file in doc/ for some minor instructions. For a quick start, download HamsterLab_bundle.zip for a ready to use version on Linux/Windows with Code::Blocks IDE and libSIGIL graphics library (pay attention to the corresponding licenses) or use HamsterLab.zip for the plain sources (GPLv3). Helpful comments are welcome :) -
Get full visibility and control over your tasks and projects with Wrike.Wrike offers world-class features that empower cross-functional, distributed, or growing teams take their projects from the initial request stage all the way to tracking work progress and reporting results.
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NYT Vote Scraper
Scrapes the NYT Votes Remaining Page JSON
...As a result, this scraper provides transparency and traceability: one can examine the “evolution of results” instead of just a snapshot. The project is inspired by the concept of “git-scraping” popularized by Simon Willison — leveraging version control to store changing datasets. -
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dualword
foreign language vocabulary trainer
DualWord is a foreign language vocabulary trainer for Linux.. Languages: English, German, French, Spanish, Russian. Source code: http://github.com/dualword/dualword/ -
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R4DS (R for Data Science)
R for data science: a book
...The repository contains the source files (Quarto / RMarkdown), example datasets, visualizations, exercises, and all content needed to build the book. Includes many example datasets, diagrams, code samples, and “hands-on” exercises. Comprehensive coverage of data-science workflow: data import, cleaning, transformation, exploration, modelling etc. Includes topics beyond basics: relational data (joins), date/time, strings, working with missing values, visualizing data, etc. -
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hubs-research-acm-chi-2021
Supplemental code and dataset for the ACM CHI 2021 paper
Supplemental code and dataset for the ACM CHI 2021 paper on "Proxemics and Social Interactions in an Instrumented Virtual Reality Workshop". In this research paper we instrumented Mozilla Hubs Cloud to record where participants where during the event. From there, we measured proxemic and plotted the activity along with some semi-structured interviews. -
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Agenda y Reservacion de Citas
Agenda y Reservacion de Citas
...La idea es que el usuario pueda seleccionar la fecha,horario y llenar datos que se le solicite, ahora con esta nueva version puede uno configurar estos datos a llenar. Aqui puedes consultar el demo: http://www.marcocantugeadev.dx.am/mcgcitasenlinea-code/AgendaElectronica/index.php Te puedes registrar y probar el sistema agergando tu correo Usuario Administrador: usuario: admin@server.com contraseña: 1234 Usuario de Administracion de Agenda Usuario:adminagenda@server.com contraseña:1234 Para instalarlo , ve a la seccion de Wiki para mas detalle o a este link: https://sourceforge.net/p/mcgcitasenlinea/wiki/Como%20Instalarlo/ -
Iris Powered By Generali - Iris puts your customer in control of their identity.Iris Identity Protection API sends identity monitoring and alerts data into your existing digital environment – an ideal solution for businesses that are looking to offer their customers identity protection services without having to build a new product or app from scratch.
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3 Rs of Software Architecture
A guide on how to write readable, reusable, and refactorable software
...It focuses on three architectural “ilities”: readability, reusability, and refactorability, presenting them in a hierarchical framework so developers can evaluate and improve their code and system design. The project uses a simple shopping-cart application written in JavaScript and React/Redux to illustrate how code evolves from “bad” via “better” to “good” across those three dimensions. By examining common smells—poor naming, deep nesting, long functions, tight coupling—readers learn how to restructure code to improve maintainability. ... -
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DeepMind Lab
A customizable 3D platform for agent-based AI research
DeepMind Lab is a 3D learning environment based on id Software's Quake III Arena via ioquake3 and other open source software. DeepMind Lab provides a suite of challenging 3D navigation and puzzle-solving tasks for learning agents. Its primary purpose is to act as a testbed for research in artificial intelligence, especially deep reinforcement learning. If you use DeepMind Lab in your research and would like to cite the DeepMind Lab environment, we suggest you cite the DeepMind Lab paper. To... -
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PH_Playground
Simple solution for testing and documenting short code snippets.
Version 4.0: improved history, error, and view mode handling Version 3.0: JavaScript editing, Quick console, History files for browsing and loading scripts. Version 2.0: CodeMirror functionality, ajax calls. Tired of opening an editor to test short code snippets for functionality, saving the file and then running it in a browser? PH_Playground provides a simple solution on a single browser page. Enter the code to be tested into the "PHP" or "JS" window and press "Run". The result will appear as Rendered or Raw HTML as you choose. In the background the code has been saved to a log file. ... -
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Python Tutorials
Machine Learning Tutorials
...It also provides tutorials on machine learning frameworks and concepts, including TensorFlow, PyTorch, Keras, Scikit-Learn, and reinforcement learning techniques. Each section contains organized code and explanations designed to help learners understand the underlying mechanics of Python and common computational approaches. -
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Tensorflow 2017 Tutorials
Tensorflow tutorial from basic to hard
...Beyond the basics, the project includes examples of convolutional neural networks, recurrent networks, autoencoders, reinforcement learning, generative adversarial networks, and transfer learning workflows. By pairing code examples with conceptual explanations, the tutorials make abstract machine learning ideas accessible and encourage experimentation with TensorBoard visualization and distributed training. -
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FFmpeg libav tutorial
FFmpeg libav tutorial
FFmpeg libav tutorial, learn how media works from basic to transmuxing, transcoding and more. Most of the code in here will be in C but don't worry: you can easily understand and apply it to your preferred language. FFmpeg libav has lots of bindings for many languages like python, go and even if your language doesn't have it, you can still support it through the ffi (here's an example with Lua). We'll start with a quick lesson about what is video, audio, codec and container and then we'll go to a crash course on how to use FFmpeg command line and finally we'll write code, feel free to skip directly to the section Learn FFmpeg libav the Hard Way. ... -
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wav2letter++
Facebook AI research's automatic speech recognition toolkit
...All results reproduction must use Flashlight <= 0.3.2 for exact reproducibility. At least one of LZMA, BZip2, or Z is required for LM compression with KenLM. It is highly recommended to build KenLM with position-independent code (-fPIC) enabled, to enable python compatibility. After installing, run export KENLM_ROOT_DIR=... so that wav2letter++ can find it. This is needed because KenLM doesn't support a make install step.wav2letter++ expects audio and transcription data to be prepared in a specific format so that they can be read from the pipelines. Each dataset (test/valid/train) needs to be in a separate file with one sample per line. ... -
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qmol
A simple molecular weight calculator
...CH3(CH2)2OH) and get its molecular weight (60.0959 g/mol) and its elemental composition (C3H8O: C 59.96; H 13.42; O 26.62 %). See the features list below for more details or consult the wiki page: https://sourceforge.net/p/qmol/wiki/Home/. For Windows binary and source code see the files section: https://sourceforge.net/projects/qmol/files/ Binary packages (rpm/deb) for openSUSE Leap 15.2-42.2, xUbuntu 20.10-19.10, 17.04, Fedora 33, CentOS 8, Scientific Linux 7, and Debian 10.0-8.0 can be found at: http://download.opensuse.org/repositories/home:/lineinthesand/ -
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IPython
Command shell for interactive computing in multiple languages
IPython provides a rich toolkit to help you make the most of using Python interactively. Comprehensive object introspection. IPython provides input history, persistent across sessions. Caching of output results during a session with automatically generated references. Extensible tab completion, with support by default for completion of python variables and keywords, filenames and function keywords. Extensible system of ‘magic’ commands for controlling the environment and performing many... -
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30 Days of Swift
A self-taught project to learn Swift
...Each “day” introduces a coding problem, concept, or mini project that builds on previous days: for example, fundamentals on day 1, optionals and control flow, Swift data structures, closures, protocol programming, UI interaction, etc., culminating in more advanced topics or sample apps. Solutions, hints, or sample projects accompany many of the prompts, allowing learners to compare approaches or download runnable code. The challenge format gives structure and pacing, helping learners stay motivated and consistent. Because the repo is public, contributors can add new challenge ideas, alternative solutions, or refinements as Swift evolves. -
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Computer Vision
Best Practices, code samples, and documentation for Computer Vision
In recent years, we've see an extra-ordinary growth in Computer Vision, with applications in face recognition, image understanding, search, drones, mapping, semi-autonomous and autonomous vehicles. A key part to many of these applications are visual recognition tasks such as image classification, object detection and image similarity. This repository provides examples and best practice guidelines for building computer vision systems. The goal of this repository is to build a comprehensive... -
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pytorch-tutorial
PyTorch Tutorial for Deep Learning Researchers
...The repository walks users through core concepts such as tensors, autograd, neural network modules, convolutional networks, recurrent networks, and transfer learning. Each section includes runnable code examples that progressively increase in complexity, helping learners build intuition while practicing hands-on implementation. Because the tutorials are concise and practical, the project is widely used in classrooms and self-study environments. Overall, it functions as both a learning curriculum and a quick reference for common PyTorch workflows. -
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Tensorflow and deep learning
A crash course in six episodes for software developers
Tensorflow and deep learning repository is an educational deep learning crash course designed to help software developers quickly understand and apply machine learning concepts without requiring advanced academic background. It is structured as a series of guided lessons that combine theoretical explanations, practical examples, and runnable code, allowing learners to build intuition while actively experimenting with models. The repository covers core neural network concepts such as weights, biases, activation functions, and gradient descent, as well as more advanced techniques like convolutional networks, recurrent networks, and reinforcement learning. It includes multiple hands-on projects, such as handwritten digit recognition, airplane detection in images, and text generation using recurrent neural networks, which demonstrate how different architectures solve real-world problems. -
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...Installation Videos! Part 1: http://youtu.be/rnv2VLcG-eI Part 2: http://youtu.be/eFudbMWHNlQ Special thanks to Wells Oliver for the code for downloading Retrosheet files. And the Chadwick project for its Retrosheet tools. https://sourceforge.net/projects/chadwick/?source=recommended
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Think Bayes
Code repository for Think Bayes
ThinkBayes is the code repository accompanying Think Bayes: a book on Bayesian statistics written in a computational style. Instead of heavy focus on continuous mathematics or calculus, the book emphasizes learning Bayesian inference by writing Python programs. The project includes code examples, scripts, and environments that correspond to the chapters of the book. -
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Python4Proteomics Course
Python course for Proteomics analysis
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
