Search Results for "processing" - Page 76
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Showing 5101 open source projects for "processing"
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Quantitative-Notebooks
Educational notebooks on quantitative finance, algorithmic trading
...The notebooks typically showcase how to perform backtesting, factor analysis, risk assessment, and other quantitative workflows in a reproducible, exploratory format. Because quantitative analysis often requires visualization, statistics, and time series processing, these notebooks also serve as templates for real financial research and strategy prototyping. Users can adapt the examples to their own data sources, financial instruments, and modeling techniques. -
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FavFreak
Favicon hash–based reconnaissance tool for security research
FavFreak is an open source reconnaissance tool designed to assist security researchers, bug bounty hunters, and penetration testers in identifying web technologies using favicon hashes. It works by taking one or more URLs as input and automatically retrieving the favicon.ico file associated with each target website. After fetching the favicon, it calculates a hash value and organizes the scanned domains, subdomains, or IP addresses according to these hashes. FavFreak then compares the... -
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Euler
A distributed graph deep learning framework.
As a general data structure with strong expressive ability, graphs can be used to describe many problems in the real world, such as user networks in social scenarios, user and commodity networks in e-commerce scenarios, communication networks in telecom scenarios, and transaction networks in financial scenarios. and drug molecule networks in medical scenarios, etc. Data in the fields of text, speech, and images is easier to process into a grid-like type of Euclidean space, which is suitable for processing by existing deep learning models. Graph is a data type in non-Euclidean space and cannot be directly applied to existing methods, requiring a specially designed graph neural network system. Graph-based learning methods such as graph neural networks combine end-to-end learning with inductive reasoning, and are expected to solve a series of problems such as relational reasoning and interpretability that deep learning cannot handle. -
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PyCBC
Learn how to use PyCBC to analyze gravitational-wave data
PyCBC is a software developed by a collaboration of LIGO, Virgo, and independent scientists. It is open source and freely available. We use PyCBC in the detection of gravitational waves from binary mergers such as GW150914. These examples explore how to analyze gravitational wave data, how we find potential signals and learn about them. Many of these tutorials will require you to make edits to config files as part of their exercises. At the moment this isn't easy to do on services like... -
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exchange-core java
Ultra-fast matching engine written in Java based on LMAX Disruptor
...HFT optimized. Priority is a limit-order-move operation mean latency (currently ~0.5µs). Cancel operation takes ~0.7µs, placing new order ~1.0µs. Pipelined multi-core processing (based on LMAX Disruptor): each CPU core is responsible for certain processing stage, user accounts shard, or symbol order books shard. -
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PyText
A natural language modeling framework based on PyTorch
PyText is a deep-learning based NLP modeling framework built on PyTorch. PyText addresses the often-conflicting requirements of enabling rapid experimentation and of serving models at scale. It achieves this by providing simple and extensible interfaces and abstractions for model components, and by using PyTorch’s capabilities of exporting models for inference via the optimized Caffe2 execution engine. We use PyText at Facebook to iterate quickly on new modeling ideas and then seamlessly... -
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uTensor
TinyML AI inference library
...Instead of training models on-device, the framework uses an offline workflow that converts trained TensorFlow graphs into optimized inference kernels suitable for constrained environments. This approach allows developers to build machine learning models using standard frameworks and then deploy them to devices with extremely limited memory and processing power. The runtime library is intentionally lightweight and optimized for platforms such as Arm Cortex-M microcontrollers, making it suitable for real-time edge applications. -
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Xi Editor
A modern editor with a backend written in Rust
...Its architecture splits a thin UI layer from a high-performance core engine (written in Rust) that handles buffer editing, syntax highlighting, undo/redo, searching, and background processing asynchronously. This separation lets the core focus on speed and concurrency, while multiple frontends (macOS, GTK, web) handle rendering, input, and platform bridging. Xi is designed to scale to huge files (gigabyte scale) without lag, thanks to a rope data structure and efficient diffing algorithms. Plugins communicate with the core via JSON-RPC, enabling asynchronous extensions without blocking editing responsiveness. ... -
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Albedo
A recommender system for discovering GitHub repos
...It treats repositories and developers as a graph of interactions and applies large-scale matrix factorization to model affinities, with Apache Spark providing the distributed data processing. The project focuses on implicit feedback—stars, watches, and other engagement metrics—so it can build useful recommendations without explicit ratings. A reproducible setup and Makefile-driven workflow streamline tasks like spinning up services, loading datasets, training models, and generating candidate lists. Because it’s built around Spark’s scalable primitives, Albedo can experiment on substantial snapshots of GitHub metadata rather than toy corpora. ... -
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Forms
An easy way to create, parse and validate forms in node.js
...Forms also provides utilities for rendering HTML form elements, reducing the need for manual template coding. It integrates with popular Node.js web frameworks, enabling seamless handling of form submissions and data processing. The design emphasizes reusability and maintainability, allowing developers to define forms once and use them across different parts of an application. -
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opencv4nodejs
Nodejs bindings to OpenCV 3 and OpenCV 4
OpenCV4NodeJS is a Node.js binding for OpenCV, allowing developers to integrate computer vision capabilities directly into JavaScript applications for image processing, object detection, and facial recognition. -
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Spectral Python
A python module for hyperspectral image processing
Spectral Python (SPy) is a python package for reading, viewing, manipulating, and classifying hyperspectral image (HSI) data. SPy includes functions for clustering, dimensionality reduction, supervised classification, and more. -
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ffmpeg.js
Port of FFmpeg with Emscripten
ffmpeg.js is a JavaScript port of the FFmpeg multimedia framework compiled with Emscripten, enabling video and audio processing directly within browsers or Node.js environments. It provides prebuilt modules optimized for web use, balancing performance and file size while supporting common encoding and decoding tasks. By running entirely in JavaScript through asm.js, it allows developers to manipulate media files without requiring native binaries or server-side processing. ... -
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G Desktop Suite
Google Suite as a desktop app. Made possible with Electron
Have you ever wished you had a no-frills, word-processing desktop app dedicated to just Google Drive? Annoyed at having to click the Go to My Drive button every time you visit drive.google? Want a Microsoft Word-esque experience for your Google Drive? Or simply looking to separate Google Drive from the other bazillion tabs that you opened for your research paper? Look no further! G Desktop Suite is a desktop wrapper for Google Drive built with ElectronJS. -
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BRIC
BRIC is a powerful tool for batch image processing.
Bric is a cross-platform batch image processor. You can convert, resize, rotate and add watermark to your images. Multiple file types are supported for input and output. The project started back in 2011 and was maintained for a couple of years. In 2020 BRIC is again in active development, so some of the features written below might be outdated. Please be patient, until everything is reviewed and rewritten. -
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DeepLearning
Deep Learning (Flower Book) mathematical derivation
...At the same time, it also introduces deep learning techniques used by practitioners in the industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling and practical methods, and investigates topics such as natural language processing, Applications in speech recognition, computer vision, online recommender systems, bioinformatics, and video games. Finally, the Deep Learning book provides research directions covering theoretical topics including linear factor models, autoencoders, representation learning, structured probabilistic models, etc. -
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JavaSeis.org: Java based software for processing and storing petroleum industry seismic data.
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EF-SKHR
Éditeur de fichier
EF-SKHR est un éditeur de fichier développé par Loyto_SKHR en C++ avec la bibliothèque QT5.9. Code source: https://github.com/Loyto-SKHR/EF-SKHR. -
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Python Crawler Tutorial Starts From Zero
Python crawler tutorial, taking you from zero to one
Python Crawler Tutorial Starts From Zero is a Chinese-language learning repository that teaches web crawling from introductory concepts through practical examples. Early lessons explain HTTP requests, request analysis, the Python Requests library, and common categories of extracted data. Separate chapters cover JSON processing and regular expressions for transforming responses into structured information. Practical exercises demonstrate crawlers for Douban movies, Baidu Tieba, and Baidu Translate. Broader project materials also address topics such as JavaScript reverse engineering, Selenium automation, OCR, MongoDB, and the Scrapy framework. Code demonstrations accompany the written lessons so readers can learn by modifying working examples. ... -
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Primitive Pictures
Reproducing images with geometric primitives
Primitive Pictures is an image processing command-line tool written in Go that reproduces images using geometric primitives (triangles, rectangles, ellipses, polygons, etc.). The core algorithm is iterative and “hill-climbing”: given a target image, it repeatedly finds the best single shape to add that will reduce the error between the current approximation and the target image, then draws that shape. -
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fastText
Library for fast text classification and representation
FastText is an open-source, free, lightweight library that allows users to learn text representations and text classifiers. It works on standard, generic hardware. Models can later be reduced in size to even fit on mobile devices. ext classification is a core problem to many applications, like spam detection, sentiment analysis or smart replies. In this tutorial, we describe how to build a text classifier with the fastText tool. The goal of text classification is to assign documents (such as... -
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qsdata
Spectral Data - binary builds for Windows 10
Small Qt based experimental program for processing spectral data. Example data are available from Files/example-data folder. -
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Monkey-DL
Bulk download your favourite anime episodes from your favourite anime
Monkey-DL is a command-line media downloader designed to retrieve video and audio content from online platforms with flexibility and automation. It integrates with tools like FFmpeg to handle post-processing tasks such as merging streams, converting formats, and optimizing output quality. The tool supports downloading single media files or entire playlists, enabling efficient batch operations. It includes options for selecting resolution, format, and output structure, giving users fine control over downloads. monkey-dl is built for simplicity, providing straightforward commands while still supporting advanced configurations. ... -
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GeoHammerToolbox
Digital Signal Processing and Wave Field Propagation
Integration of multithread calculation and 2D/3D visualization -
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Data Science at the Command Line
Data science at the command line
...To get you started, author Jeroen Janssens provides a Docker image packed with over 100 Unix power tools, useful whether you work with Windows, macOS, or Linux. You’ll quickly discover why the command line is an agile, scalable, and extensible technology. Even if you’re comfortable processing data with Python or R, you’ll learn how to greatly improve your data science workflow by leveraging the command line’s power.
