Search Results for "data collection algorithm"
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Showing 1559 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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Pythonic Data Structures and Algorithms
Minimal examples of data structures and algorithms in Python
The Pythonic Data Structures and Algorithms repository by keon is a hands-on collection of implementations of classical data structures and algorithms written in Python. It offers working, often well-commented code for many standard algorithmic problems — from sorting/searching to graph algorithms, dynamic programming, data structures, and more — making it a valuable resource for learning and reference. -
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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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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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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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Data Science Articles from CodeCut
Collection of useful data science topics along with articles
The Data-science repository from CodeCutTech is a curated collection of educational content focused on practical tools and workflows used in modern data science projects. Instead of providing a single software package, the repository aggregates articles, tutorials, and examples covering many topics within the data science ecosystem. The materials address areas such as MLOps, data management, project organization, testing practices, visualization techniques, and productivity tools used by data scientists. ... -
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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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Polymarket Data
Polymarket Data Retriever that fetches, processes, and structures data
...It begins by fetching market metadata such as questions, outcomes, and trading volumes, then proceeds to scrape order-filled events from a GraphQL-based subgraph, and finally transforms these raw events into structured trade-level records with calculated prices and directions. One of its key strengths is its ability to run incrementally and resume operations automatically, making it suitable for long-running data collection without duplication or data loss. -
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Rust Data Analysis
Rust for data analysis encyclopedia (WIP)
Welcome to the Rust Data Analysis repository! This collection of Jupyter notebooks provides a comprehensive exploration of data analysis using Rust. Powered by a Rust kernel, these notebooks allow you to dive deep into the realm of data analysis, leveraging the capabilities of the Rust programming language. With the help of various Rust libraries, such as ndarray, plotters, and more, you'll be able to extract valuable insights from different datasets with ease. -
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how-to-optim-algorithm-in-cuda
How to optimize some algorithm in cuda
how-to-optim-algorithm-in-cuda is an open educational repository focused on teaching developers how to optimize algorithms for high-performance execution on GPUs using CUDA. The project combines technical notes, code examples, and practical experiments that demonstrate how common computational kernels can be optimized to improve speed and memory efficiency. Instead of presenting only theoretical explanations, the repository includes hand-written CUDA implementations of fundamental operations... -
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The Algorithms - C++ #
Collection of various algorithms in mathematics, machine learning
TheAlgorithms/C-Plus-Plus is a large open-source repository that collects implementations of many classic algorithms and data structures written in the C++ programming language. The project is part of the broader “The Algorithms” initiative, which maintains algorithm implementations in several programming languages to support education and knowledge sharing. Within the C++ repository, contributors implement algorithms across a wide range of fields including sorting, graph theory, number theory, machine learning, cryptography, and data structures. ... -
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Hagenberg Thesis Document Collection
Hagenberg LaTeX Thesis Template
This is a collection of modern LaTeX classes, style files, and example documents for authoring Bachelor, Master, or Diploma theses and related academic manuscripts in English and German. Pre-configured English and German documents are available, easy to use even for LaTeX beginners, and compatible with LaTeX distributions for Windows, Mac OS, and Linux. The document classes are immediately usable and convenient to customize. The main document, HgbThesisTutorialEN or HgbThesisTutorialDE,... -
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AWESOME DATA SCIENCE
Awesome Data Science repository to learn and apply for real world
...They are inherently interdisciplinary. They can tackle all aspects of a problem, from initial data collection and data conditioning to drawing conclusions. -
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X For You Feed Algorithm
Algorithm powering the For You feed on X
X For You Feed Algorithm is the open-sourced core recommendation system that powers the For You feed on X (the social network formerly known as Twitter), and it represents one of the first times a major social platform has published production-level ranking code for public review and experimentation. The repository contains the full pipeline that ingests user engagement and content candidate data, processes it through retrieval, hydration, filtering, scoring, and selection layers, and ultimately ranks posts to show what appears in a user’s feed. ... -
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Data-Science-Interview-Questions-Answers
Curated list of data science interview questions and answers
Data-Science-Interview-Questions-Answers is a curated educational repository designed to help data science candidates prepare for technical interviews by organizing a large bank of questions and answers in one place. It began as a daily interview question initiative and was later consolidated into GitHub so learners could review the material more easily and revisit it over time. The repository focuses on core data science fundamentals rather than acting as a software framework, which makes... -
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Data Science Interviews
Data science interview questions and answers
Data Science Interviews is an open-source repository that collects common data science interview questions along with community-provided answers and explanations. The project serves as a preparation resource for students, job seekers, and professionals who want to review the technical knowledge required for data science roles. The repository organizes questions into different categories including theoretical machine learning concepts, technical programming questions, and probability or... -
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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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CausalInference.jl
Causal inference, graphical models and structure learning in Julia
Julia package for causal inference and analysis, graphical models and structure learning. This package contains code for the PC algorithm and the extended FCI algorithm, the score based greedy equivalence search (GES) algorithm, the Bayesian Causal Zig-Zag sampler and a function suite for adjustment set search. -
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Alibaba iLogtail
Fast and Lightweight Observability Data Collector
iLogtail was born for observable scenarios and has many production-level features such as lightweight, high performance, and automated configuration, which are widely used internally by Alibaba Group and tens of thousands of external Alibaba Cloud customers. You can deploy it in physical machines, Kubernetes and other environments to collect telemetry data, such as logs, traces and metrics. Supports a variety of Logs, Traces, and Metrics data collection, and is friendly to container and Kubernetes environment support. The resource cost of data collection is quite low, 5-20 times better than similar telemetry data collection Agent performance. High stability, used in the production of Alibaba and tens of thousands of Alibaba Cloud customers, and collecting dozens of petabytes of observable data every day with nearly tens of millions deployments. -
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ThingsBoard
Device management, data collection, processing and visualization
ThingsBoard is an open-source IoT platform for data collection, processing, visualization, and device management. It enables device connectivity via industry standard IoT protocols, MQTT, CoAP and HTTP and supports both cloud and on-premises deployments. ThingsBoard combines scalability, fault-tolerance and performance so you will never lose your data. Provision, monitor and control your IoT entities in a secure way using rich server-side APIs. -
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Machine Learning and Data Science Apps
A curated list of applied machine learning and data science notebooks
This repository is a large curated collection of machine learning and data science resources focused on real-world industry applications. Instead of being a single software framework, it acts as a knowledge base containing links to practical projects, notebooks, datasets, and libraries that demonstrate how machine learning can be applied across different sectors. The repository organizes resources by industry categories such as finance, healthcare, agriculture, manufacturing, government, and retail, allowing practitioners to explore domain-specific machine learning use cases. ... -
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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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cracking-the-data-science-interview
A Collection of Cheatsheets, Books, Questions, and Portfolio
Cracking the Data Science Interview is an open educational repository that collects study materials, resources, and reference links for preparing for data science interviews. The project organizes content across many fundamental areas of data science, including statistics, probability, SQL, machine learning, and deep learning. It includes cheat sheets that summarize important technical concepts commonly discussed during technical interviews. The repository also provides links to recommended... -
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D4RL
Collection of reference environments, offline reinforcement learning
...Researchers can load a dataset for a given task (e.g., maze navigation, manipulation) and apply their algorithm without the need to collect fresh transitions, which accelerates experimentation and comparison. The API is based on Gymnasium (via gym.make) and each environment also exposes a method get_dataset() that returns the offline data to learn from. The repository emphasizes open science, reproducibility, and benchmarking at scale, making it easier to compare algorithms on equal footing. -
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Manopt.jl
Optimization on Manifolds in Julia
Optimization Algorithm on Riemannian Manifolds. A framework to implement arbitrary optimization algorithms on Riemannian Manifolds. Library of optimization algorithms on Riemannian manifolds. Easy-to-use interface for (debug) output and recording values during an algorithm run. Several tools to investigate the algorithms, gradients, and optimality criteria.
