Search Results for "data collection algorithm"
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718 projects for "data collection algorithm" with 1 filter applied:
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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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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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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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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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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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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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Data Crow
Your collection, your way
Data Crow makes it possible. Your collection is accessible the way you prefer: as a stand-alone desktop application, in server-client mode for shared access across multiple users or devices, via the web client in any browser, or on the go with the Data Crow Reader App. The app synchronises with your Data Crow installation and works fully offline. -
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The Grand Complete Data Science Guide
Data Science Guide With Videos And Materials
The Grand Complete Data Science Materials is a repository curated by a data-science educator that aggregates a wide range of learning resources — from basic programming and math foundation to advanced topics in machine learning, deep learning, natural language processing, computer vision, and deployment practices — into a structured, centralized collection aimed at learners seeking a comprehensive path to data science mastery. -
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ML-NLP
This project is a common knowledge point and code implementation
ML-NLP is a large open-source repository that collects theoretical knowledge, practical explanations, and code examples related to machine learning, deep learning, and natural language processing. The project is designed primarily as a learning resource for algorithm engineers and students preparing for technical interviews in machine learning or NLP roles. It compiles important concepts that frequently appear in machine learning discussions, including neural network architectures, training... -
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Telegram-OSINT
https://github.com/The-Osint-Toolbox/Telegram-OSINT
...It serves as a central reference for analysts, researchers, and investigators who want to discover, analyze, and collect publicly available information from Telegram channels, groups, and bots. It organizes a wide variety of utilities that interact with Telegram’s API to gather data such as channel details, posts, and metadata, often exporting the results in formats like JSON for further analysis. The repository also includes utilities that help search for Telegram channels or process lists of channels from input files, making large-scale investigations easier to manage. In addition to direct data collection tools, it provides resources for channel discovery, similar channel analysis, and browser-based interfaces for interacting with Telegram data. -
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skycaiji
Open source web scraping system for automated data collection tasks
SkyCaiji is an open source web scraping and data collection system designed to gather information from websites through configurable extraction rules. It focuses on simplifying the process of building crawlers by allowing users to visually define scraping rules rather than writing complex code. It can collect structured or unstructured data from many types of webpages and automate the extraction process for large datasets. -
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AI Hedge Fund
An AI Hedge Fund Team
This repository demonstrates how to build a simplified, automated hedge fund strategy powered by AI/ML. It integrates financial data collection, preprocessing, feature engineering, and predictive modeling to simulate decision-making in trading. The code shows workflows for pulling stock or market data, applying machine learning algorithms to forecast trends, and generating buy/sell/hold signals based on the predictions. Its structure is educational: intended more as a proof-of-concept than a ready-to-use financial product, giving learners insight into the mechanics of quantitative finance automation. ... -
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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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cobalt
Video and media downloader: Best way to save what you love
...The project is built with performance in mind, leveraging efficient backend processing to handle requests quickly and consistently. It also prioritizes user privacy by avoiding data collection and minimizing external dependencies. Cobalt is designed to be simple yet powerful, offering a streamlined interface while still supporting a wide range of media sources and formats. Its architecture allows for easy deployment and customization, making it suitable for both personal use and integration into larger systems. -
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douyin
Open source Douyin crawler for collecting and downloading public data
DouyinCrawler is an open source data collection tool designed to gather publicly available information from the Douyin platform. It demonstrates how to build a Python-based web crawler combined with a graphical interface and command line functionality. It allows users to collect data from various types of Douyin content, including user profiles, videos, hashtags, and music pages. -
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Hacks
A collection of hacks and one-off scripts
Hacks is a collection of experimental scripts, utilities, and one-off tools created to solve specific problems in security research, data processing, and automation. Rather than being a single cohesive application, it serves as a repository of practical command-line tools that can be used independently or combined into workflows. The scripts cover a wide range of tasks, including URL manipulation, parameter replacement, data extraction, and reconnaissance automation. ... -
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Complete-Python-3-Bootcamp
Course Files for Complete Python 3 Bootcamp Course on Udemy
The Complete-Python-3-Bootcamp repository is an educational resource created by Pierian Data as part of their popular Python for Data Science and Machine Learning Bootcamp course. It contains a comprehensive collection of Jupyter Notebooks designed to teach Python programming from the ground up. The repository covers a wide range of Python topics, including data types, control flow, functions, object-oriented programming, error handling, modules, and advanced concepts like decorators and generators. ... -
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LeetCode Animation
Demonstrate all the questions on LeetCode in the form of animation
LeetCodeAnimation is an educational open source project by MisterBooo that visually demonstrates algorithm problems from LeetCode through animations. The goal of the project is to help learners understand complex algorithmic concepts intuitively by showing step-by-step animated explanations instead of relying solely on static code or text. Each animation corresponds to a specific problem and illustrates how data structures and algorithms operate dynamically, making it easier to grasp their underlying logic. ... -
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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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OmniTools
Self-hosted collection of powerful web-based tools for everyday tasks
OmniTools is a self-hosted web application that bundles a large collection of everyday utilities into a single clean interface you can run on your own infrastructure. It’s designed to replace the random assortment of “free online tools” people use for quick tasks, while avoiding ads, tracking, and the need to upload sensitive files to unknown servers. A key design choice is that file processing happens entirely on the client side, meaning your data stays in your browser instead of being sent to the backend. ...
