Search Results for "data collection algorithm" - Page 2
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Showing 1563 open source projects for "data collection algorithm"
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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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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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harmonypy
Integrate multiple high-dimensional datasets with fuzzy k-means
Harmony is an algorithm for integrating multiple high-dimensional datasets. harmonypy is a port of the harmony R package by Ilya Korsunsky. Harmony is a general-purpose R package with an efficient algorithm for integrating multiple data sets. It is especially useful for large single-cell datasets such as single-cell RNA-seq. -
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UMAP.jl
Uniform Manifold Approximation and Projection (UMAP) implementation
A pure Julia implementation of the Uniform Manifold Approximation and Projection dimension reduction algorithm. The umap function takes two arguments, X (a column-major matrix of shape (n_features, n_samples)), n_components (the number of dimensions in the output embedding), and various keyword arguments. -
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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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TikZ
TikZ figures for concepts in physics/chemistry/ML
Collection of 111 standalone TikZ figures for illustrating concepts in physics, chemistry, and machine learning. Check out janosh.github.io to search, sort, open in Overleaf, and download figures (PDF/SVG/PNG) from this collection. -
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Brotli
Brotli compression format
...This happens when "one-shot" decoding API is used (or input chunk for streaming API is not limited), input size (chunk size) is larger than 2GiB, and input contains uncompressed blocks. After the overflow happens, memcpy is invoked with a gigantic num value, that will likely cause the crash. Brotli is a generic-purpose lossless compression algorithm that compresses data using a combination of a modern variant of the LZ77 algorithm, Huffman coding and 2nd order context modeling, with a compression ratio comparable to the best currently available general-purpose compression methods. It is similar in speed with deflate but offers more dense compression. The specification of the Brotli Compressed Data Format is defined in RFC 7932. ... -
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MIRT.jl
MIRT: Michigan Image Reconstruction Toolbox (Julia version)
MIRT.jl is a collection of Julia functions for performing image reconstruction and solving related inverse problems. It is very much still under construction, although there are already enough tools to solve useful problems like compressed sensing MRI reconstruction. Trying the demos is a good way to get started. The documentation is even more still under construction. -
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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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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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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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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. ... -
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Spotube
Open source Spotify client that doesn't require Premium
An open source, cross-platform Spotify client compatible across multiple platforms utilizing Spotify's data API and YouTube, Piped video or JioSaavn as an audio source, eliminating the need for Spotify Premium. It is still recommended to support creators by engaging with their YouTube channels/Spotify tracks (or preferably by buying their merch/concert tickets/physical media). -
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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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Coluna.jl
Branch-and-Price-and-Cut in Julia
Coluna is a branch-and-price-and-cut framework written in Julia. You write an original MIP that models your problem using the JuMP modeling language and our specific extension BlockDecomposition offers a syntax to specify the problem decomposition. Then, Coluna reformulates the original MIP and optimizes the reformulation using the algorithms you choose. Coluna aims to be very modular and tweakable so that you can define the behavior of your customized branch-and-price-and-cut algorithm. -
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Parsers.jl
fast parsing machinery for basic types in Julia
A collection of type parsers and utilities for Julia. Installation: at the Julia REPL, import Pkg; Pkg.add("Parsers") Parsers is maintained collectively by the JuliaData collaborators. Responsiveness to pull requests and issues can vary, depending on the availability of key collaborators. -
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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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Clustering.jl
A Julia package for data clustering
Methods for data clustering and evaluation of clustering quality. -
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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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openTSNE
Extensible, parallel implementations of t-SNE
openTSNE is a modular Python implementation of t-Distributed Stochasitc Neighbor Embedding (t-SNE) [1], a popular dimensionality-reduction algorithm for visualizing high-dimensional data sets. openTSNE incorporates the latest improvements to the t-SNE algorithm, including the ability to add new data points to existing embeddings [2], massive speed improvements [3] [4] [5], enabling t-SNE to scale to millions of data points, and various tricks to improve the global alignment of the resulting visualizations. -
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DouK-Downloader
TikTok releases/likes/compilations/live streams/videos/atlases/music
...The software goes beyond simple downloading by offering comprehensive data collection features, including comments, user statistics, and trending data such as hot boards and search results. It supports automated workflows like incremental downloads, duplicate detection, and persistent storage of collected data in formats like CSV, XLSX, and SQLite, making it useful for both content archiving and analytics. -
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Jellyfin
The Free Software Media System
...Jellyfin enables you to collect, manage, and stream your media. Run the Jellyfin server on your system and gain access to the leading free-software entertainment system, bells and whistles included. Hold your entire movie collection, with a beautiful collection of posters. Jellyfin lets you watch your media from a web browser on your computer, apps on your Roku, Android, iOS (including AirPlay), Android TV, or Fire TV device, or via your Chromecast or existing Kodi installation. Jellyfin has no tracking, phone-home, or central servers collecting your data. ... -
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GeoLibre
A lightweight, cloud-native GIS platform
...It also includes advanced tools such as multi-map comparison, SQL workspaces, story maps, field collection, plugins, Python automation, and an AI GIS assistant. -
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GTweak
Portable Tool for an Ideal Windows Setup
...GTweak also includes features for removing pre-installed apps, managing updates, and customizing the Windows interface. It is particularly focused on privacy, enabling users to disable tracking, data collection, and background services from Microsoft and third parties. Overall, GTweak serves as an all-in-one toolkit for debloating, securing, and optimizing Windows environments. -
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LAStools
efficient tools for LiDAR processing
LAStools is a collection of efficient, multi-core, scriptable tools for processing LiDAR data. It supports various formats, including LAS, LAZ, Terrasolid BIN, and ESRI Shapefiles, providing a comprehensive suite for LiDAR data management and analysis.