Search Results for "data collection algorithm"
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Showing 398 open source projects for "data collection algorithm"
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Hello Algorithm
Animated illustrations, one-click data structure
Animated illustrations, one-click data structure and algorithm tutorials. This project aims to create an open source, free, novice-friendly introductory tutorial on data structures and algorithms. The whole book uses animated illustrations, the content is clear and easy to understand, and the learning curve is smooth, guiding beginners to explore the knowledge map of data structures and algorithms. -
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Swift Algorithm Club
Algorithms and data structures in Swift, with explanations
Swift Algorithm Club is a project that implements a broad collection of algorithms and data structures in the Swift programming language, with clear commentary and educational intent. Its purpose is not primarily to be a utility library, but rather to teach the how and why behind algorithms—readers can study implementations, complexity, and design choices in a Swift context. -
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Dynamic Data
Reactive collections based on Rx.Net
...Dynamic data has been developed to remove the tedious code of dynamically maintaining collections. It has grown to become functionally very rich with at least 60 collection-based operations which amongst other things enable filtering, sorting, grouping, joining different sources, transforms, binding, pagination, data virtualization, expiration, disposal management plus more. -
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JavaScript Algo and Data Structures
Algorithms and data structures implemented in JavaScript
javascript-algorithms is an open source repository by Oleksii Trekhleb that provides implementations of algorithms and data structures in JavaScript. Each algorithm includes explanations, complexity analysis, and references for further reading, making it both a coding resource and a study guide. The repository covers topics such as sorting, searching, graph algorithms, cryptography, and data structures like linked lists, stacks, and queues. It is designed to help developers understand algorithm fundamentals and practice problem-solving with JavaScript. ... -
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Spring Data REST
Simplifies building hypermedia-driven REST web services
Spring Data REST is part of the umbrella Spring Data project and makes it easy to build hypermedia-driven REST web services on top of Spring Data repositories. Spring Data REST builds on top of Spring Data repositories, analyzes your application’s domain model and exposes hypermedia-driven HTTP resources for aggregates contained in the model. -
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X's Recommendation Algorithm
Source code for the X Recommendation Algorithm
The Algorithm is Twitter’s open source release of the core ranking system that powers the platform’s home timeline. It provides transparency into how tweets are selected, prioritized, and surfaced to users, reflecting Twitter’s move toward openness in recommendation algorithms. The repository contains the recommendation pipeline, which incorporates signals such as engagement, relevance, and content features, and demonstrates how they combine to form ranked outputs. -
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Spring Data Redis
Provides support to increase developer productivity in Java
Provides support to increase developer productivity in Java when using Redis, a key-value store. Uses familiar Spring concepts such as a template class for core API usage and lightweight repository-style data access. The primary goal of the Spring Data project is to make it easier to build Spring-powered applications that use new data access technologies such as non-relational databases, map-reduce frameworks, and cloud-based data services. Connection package as low-level abstraction across... -
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Zstandard
Zstandard - Fast real-time compression algorithm
Zstandard is a fast compression algorithm, providing high compression ratios. It also offers a special mode for small data, called dictionary compression. The reference library offers a very wide range of speed / compression trade-off, and is backed by an extremely fast decoder (see benchmarks below). Zstandard library is provided as open source software using a BSD license. -
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Zipkin
Distributed tracing system to gather timing data
Zipkin is a distributed tracing system. It helps gather timing data needed to troubleshoot latency problems in service architectures. Features include both the collection and lookup of this data. If you have a trace ID in a log file, you can jump directly to it. Otherwise, you can query based on attributes such as service, operation name, tags and duration. Some interesting data will be summarized for you, such as the percentage of time spent in a service, and whether or not operations failed. ... -
Build Securely on AWS with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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WaterfallGrid
A waterfall grid layout view for SwiftUI
A waterfall grid layout view for SwiftUI. You can create a grid that displays the elements of the collection by passing your collection of data and a closure that provides a view for each element in the collection. The grid transforms each element in the collection into a child view by using the supplied closure. WaterfallGrid works with identifiable data (like SwiftUI.List). You can make your data identifiable in one of two ways: by passing along with your data a key path to a property that uniquely identifies each element, or by making your data type conform to the Identifiable protocol. ... -
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Go Recipes
Collection of handy tools for Go projects
Visualize the distribution of code coverage in your project. This helps to identify code areas with high and low coverage. Useful when you have a large project with lots of files and packages. This 2D image-hash of your project should be more representative than a single number. For each module, the node representing the greatest version (i.e., the version chosen by Go's minimal version selection algorithm) is colored green. Other nodes, which aren't in the final build list, are colored grey... -
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Immutable.js
Immutable collections for JavaScript
Immutable.js offers a collection of Persistent Immutable data structures for JavaScript. Immutable data is unchangeable once created, which makes application development so much simpler. There’s no defensive copying, and you get advanced memoization and change detection techniques with simple logic. Persistent data gives you a mutative API, one that doesn’t update data in-place but always produces new and updated data. -
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lockfree
A collection of lock-free data structures written in standard C++11
lockfree is a collection of lock-free data structures written in standard C++11 and suitable for all platforms - from deeply embedded to HPC. Lock-free data structures are data structures that are thread and interrupt-safe for concurrent use without having to use mutual exclusion mechanisms. They are most useful for inter-process communication and often scale much better than lock-based structures with the number of operations and threads. -
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CodeGuide
This repository is a collection of the author, Xiao Fuge
CodeGuide is a curated collection of Java development resources built from years of real-world engineering experience by the author, who has worked extensively in large-scale internet companies. The project serves as a structured and comprehensive learning path for developers who want to strengthen their understanding of Java fundamentals and core programming practices. It includes detailed explanations of design patterns, source code analysis, frameworks, algorithms, and real-world project... -
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CPlusPlusThings
Collection of various C++ code samples, utilities, patterns
CPlusPlusThings is a repository collecting various C++ code samples, utilities, patterns, and small example projects. It is less a polished product and more a learning/reference collection of snippets and usages of C++ idioms, data structures, algorithms, utilities, and perhaps tricks or meta-programming exercises. (No prominent README or detailed docs were available from my quick search.) Example implementations of data structures and algorithms. Organized as a learning repository (rather than a production framework). ... -
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Deepchecks
Test Suites for validating ML models & data
Deepchecks is the leading tool for testing and for validating your machine learning models and data, and it enables doing so with minimal effort. Deepchecks accompany you through various validation and testing needs such as verifying your data’s integrity, inspecting its distributions, validating data splits, evaluating your model and comparing between different models. While you’re in the research phase, and want to validate your data, find potential methodological problems, and/or validate your model and evaluate it. ... -
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LZ4
Extremely fast compression algorithm
LZ4 is lossless compression algorithm, providing compression speed > 500 MB/s per core (>0.15 Bytes/cycle). It features an extremely fast decoder, with speed in multiple GB/s per core (~1 Byte/cycle). A high compression derivative, called LZ4_HC, is available, trading customizable CPU time for compression ratio. LZ4 library is provided as open-source software using a BSD license. -
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IGListKit
A data-driven UICollectionView framework for building fast lists
IGListKit uses an algorithm adapted from a paper titled A technique for isolating differences between files by Paul Heckel. This algorithm uses a technique known as the longest common subsequence to find a minimal diff between collections in linear time O(n). It finds all inserts, deletes, updates, and moves between arrays of data. A working range is a range of section controllers who aren’t yet visible, but are near the screen. -
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xxHash
Extremely fast non-cryptographic hash algorithm
...Code is highly portable, and hashes are identical across all platforms (little / big endian). Performance on large data is only one part of the picture. Hashing is also very useful in constructions like hash tables and bloom filters. In these use cases, it's frequent to hash a lot of small data (starting at a few bytes). Algorithm's performance can be very different for such scenarios, since parts of the algorithm, such as initialization or finalization, become fixed cost. ... -
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Doctrine Collections
Collections abstraction library
Doctrine Collections is a library that contains classes for working with arrays of data. Doctrine Collections provides an interface named Doctrine\Common\Collections\Collection that resembles the nature of a regular PHP array. That is, it is essentially an ordered map that can also be used like a list. A Collection has an internal iterator just like a PHP array. In addition, a Collection can be iterated with external iterators, which is preferable. -
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Homemade Machine Learning
Python examples of popular machine learning algorithms
homemade-machine-learning is a repository by Oleksii Trekhleb containing Python implementations of classic machine-learning algorithms done “from scratch”, meaning you don’t rely heavily on high-level libraries but instead write the logic yourself to deepen understanding. Each algorithm is accompanied by mathematical explanations, visualizations (often via Jupyter notebooks), and interactive demos so you can tweak parameters, data, and observe outcomes in real time. The purpose is pedagogical: you’ll see linear regression, logistic regression, k-means clustering, neural nets, decision trees, etc., built in Python using fundamentals like NumPy and Matplotlib, not hidden behind API calls. ... -
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LeetCode Master
About "Code Thoughts" LeetCode Practice Guide: 200 classic questions
...Each solution is accompanied by clear commentary to explain the thought process, algorithm design, and complexity analysis. The project is continuously updated and widely used by learners as both a reference and a roadmap to progress from beginner to advanced LeetCode practice. With its thorough coverage and educational style, leetcode-master helps programmers build strong problem-solving skills and confidence for competitive programming. -
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Loggie
A lightweight, cloud-native data transfer agent and aggregator
Loggie is a lightweight, high-performance, cloud-native agent and aggregator based on Golang. Loggie includes LogConfig/ClusterLogConfig/Interceptor/Sink CRDs, allowing for the creation of data collection, transfer, processing, and sending pipelines through simple YAML file creation. Supports deployment as an independent intermediate machine, which can receive aggregated data sent by Loggie Agent and can also be used to consume and process various data sources. Configure Filebeat and Loggie to collect logs, and send them to a Kafka topic without using client compression, with the Kafka topic partition configured as 3. ... -
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google-java-format
Reformats Java source code to comply with Google Java Style
google-java-format is a program that reformats Java source code to comply with Google Java Style. The formatter can act on whole files, on limited lines, on specific offsets, passing through to standard-out (default) or altered in-place. There is no configurability as to the formatter's algorithm for formatting. This is a deliberate design decision to unify our code formatting on a single format. The formatter can be used in software that generates java to output more legible java code. Just... -
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Laravel Fractal
An easy to use Fractal wrapper built for Laravel and Lumen
The package provides a nice and easy wrapper around Fractal for use in your Laravel applications. If you don't know what Fractal does, take a peek at their intro. Shortly said, Fractal is very useful to transform data before using it in an API. Transforming right from a Laravel collection is particularly useful for Eloquent results. You can transform directly from a Laravel collection as well. There's also a very short syntax available to quickly transform data. Lovers of facades will be glad to know that a facade is provided. You can add methods to the Fractal class using Laravel's Macroable trait. ...
