Search Results for "data collection algorithm" - Page 4
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Showing 153 open source projects for "data collection algorithm"
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cppcrypto
C++ cryptographic library (modern hash functions, ciphers, KDFs)
cppcrypto provides optimized implementations of cryptographic primitives. Hash functions: BLAKE, BLAKE2, Echo, Esch, Groestl, JH, Kupyna, MD5, SHA-1, SHA-2, SHA-3, SHAKE, Skein, SM3, Streebog, Whirlpool. Block ciphers: Anubis, Aria, Camellia, CAST-256, Kalyna, Kuznyechik, Mars, Serpent, Simon, SM4, Speck, Threefish, Twofish, and Rijndael (AES) with all block/key sizes. Stream ciphers: HC-128, HC-256, Salsa20, XSalsa20, ChaCha, XChaCha. Encryption modes: CBC, CTR. AEAD modes:... -
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Sandia Cyber Omni Tracker
Sandia Cyber Omni Tracker (SCOT)
SCOT is an open-source cybersecurity incident response and threat intelligence management system developed by Sandia National Laboratories. It centralizes alert collection, facilitates team collaboration, and enriches data with automated analysis, enhancing the efficiency and effectiveness of security operations teams. -
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Jraph
A Graph Neural Network Library in Jax
Jraph (pronounced “giraffe”) is a lightweight JAX library developed by Google DeepMind for building and experimenting with graph neural networks (GNNs). It provides an efficient and flexible framework for representing, manipulating, and training models on graph-structured data. The core of Jraph is the GraphsTuple data structure, which enables users to define graphs with arbitrary node, edge, and global attributes, and to batch variable-sized graphs efficiently for JAX’s just-in-time compilation. The library includes a comprehensive set of utilities for batching, padding, masking, and partitioning graph data, making it ideal for distributed and large-scale GNN experiments. ... -
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Guide to Technical Interviews
Guided collection and roadmap for preparing technical interviews
This repository is a guided collection and roadmap for preparing technical interviews, covering the gamut from algorithmic challenges and data structures to system design and behavioral preparation. It consolidates resources like interview question lists, practice platforms, mock interview sites, and recommended books or blogs. For individuals targeting big-tech or rigorous interview processes, this acts as a structured study guide rather than a random list of links. -
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Julia.jl
Curated decibans of Julia programming language
Julia.jl is a curated collection of knowledge resources for the Julia programming language, designed to support high-performance numerical analysis and computational science. The repository aggregates diverse content across domains such as mathematics, physics, data science, optimization, machine learning, and supercomputing. It functions as a structured index, helping developers, researchers, and learners easily find materials to deepen their understanding of Julia’s ecosystem. ... -
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comby
A code rewrite tool for structural search and replace that supports
Comby is a tool for searching and changing code structure. Use lightweight templates to easily search and change code, HTML, or JSON. Comby is designed to work on any language or data format. Perform richer search and replace because Comby understands the syntax of code blocks, strings, and comments for your language. Comby is ideal for touching up pieces of code. Use it to translate code like this Python 2 to 3 fixer on the right to replace deprecated methods. Easily write one-off refactors or a collection of quick fixes customized to your project. ... -
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LeetCode
LeetCode Problems' Solutions
LeetCode is a long-running repository of solutions to LeetCode programming problems. It is organized as a study and reference collection for algorithm practice, technical interview preparation, and problem-solving review. The repository includes implementations for many classic coding challenge categories such as arrays, strings, linked lists, trees, graphs, dynamic programming, sorting, searching, and math. It is useful for comparing approaches, reviewing solution patterns, and studying how common interview problems can be implemented in code. ... -
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Differ
Swift library to generate differences and patches between collections
Differ generates the differences between Collection instances. There’s a lot more to calculating diffs than performing table view animations easily. Wherever you have code that propagates added/removed/moved callbacks from your model to your user interface, you should consider using a library that can calculate differences. Animating small batches of changes is usually going to be faster and provide a more responsive experience than reloading all of your data. -
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Pythonidae
Curated decibans of scientific programming resources in Python
...The project emphasizes open contribution, allowing the community to continuously expand and refine the index. By gathering these resources in one place, Pythonidae acts as a central hub for scientific and data-driven programming with Python. -
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TensorFlow Examples
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
TensorFlow Examples is a comprehensive repository of example implementations, tutorials, and reference code intended to help newcomers and intermediate learners dive into TensorFlow quickly. It contains both Jupyter notebooks and raw source code, covering a broad range of tasks: from basic machine-learning and neural-network models to more advanced use cases, using both TensorFlow v1 and v2 APIs. For clarity and educational value, each example is accompanied by explanatory comments or... -
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Awfice
The world smallest office suite
...It includes a rich-text editor, spreadsheet, drawing canvas, and presentation maker. Every main tool is under one kilobyte and is compressed into a single line of code. The applications can run directly from data URLs, bookmarks, or saved HTML files without installation. They work offline and intentionally avoid persistent storage, so refreshing the page erases the current content. The spreadsheet supports formulas and cell references, while the presentation tool offers editable slides and formatting shortcuts. Awfice is both a code-golf demonstration and a practical collection of disposable scratchpads for quick, private work. -
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ReinventCommunity
Jupyter Notebook tutorials for REINVENT 3.2
This repository is a collection of useful jupyter notebooks, code snippets and example JSON files illustrating the use of Reinvent 3.2. -
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DeepDiff
Amazingly incredible extraordinary lightning fast diffing in Swift
DeepDiff is a Swift library for efficiently calculating differences between collections and models. It is designed for iOS, macOS, and Swift developers who need fast diffing when updating lists, tables, collection views, or other ordered data displays. The library relies on models conforming to a diff-aware protocol so items can be uniquely identified and compared. This makes it useful for deciding which elements were inserted, deleted, moved, or replaced between two versions of a dataset. DeepDiff helps reduce unnecessary UI reloads by making updates more targeted and animation-friendly. ... -
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BMC
Notes on Scientific Computing for Biomechanics
This repository is a collection of lecture notes and code on scientific computing and data analysis for Biomechanics and Motor Control. -
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earthengine-py-notebooks
A collection of 360+ Jupyter Python notebook examples
earthengine-py-notebooks is a comprehensive collection of hundreds of Jupyter Python notebooks that serve as examples and tutorials for using the Google Earth Engine Python API. These notebooks are organized into thematic areas such as image processing, machine learning, visualization, filtering, and asset management, exposing users to real geospatial analysis tasks. The repository makes it easier to explore Earth Engine’s large geospatial data catalog, interactively display map layers, and generate visual insights without the need for external GIS software by leveraging interactive widgets and mapping libraries. ... -
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Essentials
General purpose utilities and hash functions for Android and Java
Essentials is a lightweight collection of high-performance utility classes designed to enhance standard Java and Android development without introducing heavy dependencies. The library focuses on providing efficient data structures and helper utilities that often outperform equivalent components in the standard Java API. It is intentionally minimalistic and is not positioned as a full framework, but rather as a focused toolkit that fills common gaps developers encounter in everyday projects. ... -
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Zipline
Zipline, a Pythonic algorithmic trading library
Zipline is a Pythonic algorithmic trading library. It is an event-driven system for backtesting. Zipline is currently used in production as the backtesting and live-trading engine powering Quantopian -- a free, community-centered, hosted platform for building and executing trading strategies. Quantopian also offers a fully managed service for professionals that includes Zipline, Alphalens, Pyfolio, FactSet data, and more. Installing Zipline is slightly more involved than the average Python... -
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HeyUI.ext
UI Toolkit for Web, Vue3.0
HeyUI.ext is a comprehensive UI component library built for Vue.js that provides a wide range of reusable components and tools for developing modern web applications with efficiency and consistency. Designed as a full UI toolkit rather than a minimal component set, it includes elements for forms, tables, modals, navigation, and data handling, making it suitable for building complex interfaces such as dashboards and admin panels. The library emphasizes simplicity and speed, allowing... -
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Forecasting Best Practices
Time Series Forecasting Best Practices & Examples
Time series forecasting is one of the most important topics in data science. Almost every business needs to predict the future in order to make better decisions and allocate resources more effectively. This repository provides examples and best practice guidelines for building forecasting solutions. The goal of this repository is to build a comprehensive set of tools and examples that leverage recent advances in forecasting algorithms to build solutions and operationalize them. Rather than... -
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ebfformat
An Efficient Binary data Format
...It is also designed to simplify the programming of input output routines in different programming languages. In a nutshell an EBF file is a collection of data objects. Each data object is specified by a unique name and a single file can have multiple data objects. Each data object is preceded by a meta-data or header which describes the binary data associated with it. Among other things, this header allows the files to be portable across systems with different endianess. -
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libreact
Collection of useful React components
libreact is a collection of reusable React components and utilities — described as a “standard library for React projects” — that aims to simplify and standardise common patterns in React development. The library is modular: you can import specific modules such as withState, withToggle, mock, loadable, lazy, flipflop, withValue, List, Map, sensors, toggles and more. Many components are isomorphic (work in browser and server) and some even support React Native. It comes with documentation and... -
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The Neural Process Family
This repository contains notebook implementations
Neural Processes (NPs) is a collection of interactive Jupyter/Colab notebook implementations developed by Google DeepMind, showcasing three foundational probabilistic machine learning models: Conditional Neural Processes (CNPs), Neural Processes (NPs), and Attentive Neural Processes (ANPs). These models combine the strengths of neural networks and stochastic processes, allowing for flexible function approximation with uncertainty estimation. -
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Happy Java Library
Multilock, Collections, Controllers, Delegates, Generators, Streams
Helps to develop and test event-based multi-threaded Java application. Because of method called as API-Evolution the Happy Java Library is fully downward compatible. The library contains following functionality: MultiLock, Parallel loops, Collections, Controllers, Generators, Delegates, Streams. -
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RecNN
Reinforced Recommendation toolkit built around pytorch 1.7
This is my school project. It focuses on Reinforcement Learning for personalized news recommendation. The main distinction is that it tries to solve online off-policy learning with dynamically generated item embeddings. I want to create a library with SOTA algorithms for reinforcement learning recommendation, providing the level of abstraction you like. -
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AES Everywhere
Cross Language AES 256 Encryption Library
AES Everywhere is Cross Language Encryption Library that provides the ability to encrypt and decrypt data using a single algorithm in different programming languages and on different platforms. This is an implementation of the AES algorithm, specifically CBC mode, with 256-bit key length and PKCS7 padding. It implements OpenSSL-compatible cryptography with randomly generated salt.
