Search Results for "data collection algorithm" - Page 11
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582 projects for "data collection algorithm" with 1 filter applied:
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Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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$300 Free Credits for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
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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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COHCAP
City of Hope CpG Island Analysis Pipeline
COHCAP (City of Hope CpG Island Analysis Pipeline, pronounced "co-cap") is an algorithm to analyze single-nucleotide resolution methylation data (Illumina 450k methylation array, targeted BS-Seq, etc.). Please note: 1) The SourceForge version of COHCAP is no longer being updated. Please see the GitHub version: https://github.com/cwarden45/COHCAP This was the source repository for the Bioconductor version, with some changes after the decision to only provide the code through GitHub. 2) In addition to the original NAR paper, please see the following links: Benchmarks: http://www.nature.com/protocolexchange/protocols/2965#/introduction Protocol Exchange Files: http://sourceforge.net/projects/cohcap/files/Protocol_Exchange_Example.zip 3) Custom Annotation Files (including EPIC Array): https://sourceforge.net/projects/cohcap/files/additional_Bioconductor_annotations.zip/download -
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GoogleScraper
Python tool for scraping search engine results from many providers
GoogleScraper is a Python-based tool designed to automatically collect and process search engine results from multiple providers. It enables developers and researchers to programmatically query search engines and extract useful information such as links, titles, and result descriptions. GoogleScraper supports several major search engines and can be used to gather structured datasets from search result pages for further analysis. It provides two different scraping approaches: sending direct... -
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MyJaPhoO My Java Photo Organizer Manages local Photo and Video Collections
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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Machine Learning Homework
Matlab Coding homework for Machine Learning
The Machine-Learning-homework repository by user “Ayatans” is a collection of MATLAB code intended to solve or illustrate assignments in machine learning courses. It includes implementations of standard machine learning algorithms (such as regression, classification, etc.), scripts for data loading and preprocessing, and evaluation routines (e.g. accuracy, error metrics). Because it is structured as homework or practice material, the code is likely intended more for didactic use than for production deployment. ... -
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Flip card learning program for iPhone with a spaced learning algorithm. Create your own databases and edit the cards directly on the iPhone. Import Palm databases or csv-formatted files and backup your data with our Java application.
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TArray
Typed Arrays for Tcl
TArray is a Tcl extension that implements typed arrays. The primary motivation is to minimize memory usage and parallelize operations when dealing with large data sets. TArray provides a raw array data type that can then be scripted to provide more sophisticated collection structures. -
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Blazorise
Blazorise is a component library built on top of Blazor
Blazorise is a modern, extensible UI component library designed for building rich web applications using Microsoft’s Blazor framework and the .NET ecosystem. It provides a comprehensive suite of reusable UI components that allow developers to create consistent, responsive, and scalable interfaces without manually implementing common patterns. One of its defining features is its provider-based architecture, which decouples component logic from visual styling, enabling developers to switch... -
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RL-Stock
Automated stock trading through a simulated training environment
RL-Stock is a reinforcement learning project that explores automated stock trading through a simulated training environment. It is written as an educational experiment rather than a financial product or investment recommendation system. The project includes scripts for collecting stock data, defining a reinforcement learning environment, training an agent, and visualizing results. It focuses on how an agent can learn trading-like behavior through rewards, states, and actions. The repository... -
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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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AhoCorasickDoubleArrayTrie
An extremely fast implementation of Aho Corasick algorithm
AhoCorasickDoubleArrayTrie is a Java implementation of the Aho–Corasick multi-pattern matching algorithm that is optimized using a Double-Array Trie data structure. It is designed for fast keyword scanning across large texts, where you want to search for many patterns simultaneously and efficiently. The core idea is to build an automaton from a dictionary of patterns, then stream through input text to emit matches with minimal overhead. -
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Literature of Deep Learning for Graphs
A comprehensive collection of recent papers on graph deep learning
...The collection includes foundational works that introduced graph convolutional networks as well as more recent research on large-scale graph representation learning and graph generation techniques. The repository is designed as a reference guide for students and researchers who want to explore the rapidly growing field of graph deep learning. -
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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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AutoAni
Compilation-free adaptive swf visualization template
AutoAni is a compilation-free adaptive visualization template designed for creating animated bar chart races and similar time-based visualizations using Flash. It focuses on ease of use for beginners by removing the need to install Flash or compile code—users simply prepare their data and images, place them in the same directory, and open the provided SWF file with any compatible player. The template comes with built-in Source Han Sans fonts, ensuring consistent text rendering without... -
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Common Music
An algorithmic music composition system
Common Music (CM) is a real-time music composition system implemented in JUCE/C++ and Scheme. It generates musical output via MIDI, OSC, CLM, FOMUS and CSOUND. Its user application is called GRACE (Graphical Real-time Algorithmic Composition Environment) -
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Scikit-learn Tutorial
An introductory tutorial for scikit-learn
Scikit-learn Tutorial contains the materials for Jake VanderPlas’s introductory scikit-learn tutorial, originally used at major Python conferences. It provides a collection of notebooks that walk attendees from basic machine-learning concepts into practical modeling using the scikit-learn library. The tutorial covers data preparation, model fitting, evaluation, and common algorithms such as classification, regression, clustering, and dimensionality reduction. It is designed for people who already have a working Python environment and some familiarity with NumPy, SciPy, and Matplotlib. ... -
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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. -
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AI Cheatsheets
Essential Cheat Sheets for deep learning and machine learning research
cheatsheets-ai is an open-source repository that collects essential cheat sheets covering many tools and concepts used in machine learning, deep learning, and data science. The project aims to provide quick-reference materials that help engineers, researchers, and students review key techniques and frameworks without reading extensive documentation. It compiles cheat sheets for widely used libraries and technologies such as TensorFlow, Keras, NumPy, Pandas, Scikit-learn, Matplotlib, and... -
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nlp_chinese_corpus
Large Scale Chinese Corpus for NLP
nlp_chinese_corpus is a large-scale Chinese corpus collection for natural language processing research and development. It was created to make high-volume Chinese text data easier to access for students, researchers, and practitioners. The repository gathers several major datasets, including Chinese Wikipedia entries, news articles, encyclopedia-style question answering data, community question answering data, and Chinese-English translation sentence pairs. ... -
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benchm-ml
A benchmark of commonly used open source implementations
...The repository is structured in logical folders, each corresponding to algorithm categories. -
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CCZero (中国象棋Zero)
Implement AlphaZero/AlphaGo Zero methods on Chinese chess
ChineseChess-AlphaZero is a project that implements the AlphaZero algorithm for the game of Chinese Chess (Xiangqi). It adapts DeepMind’s AlphaZero method—combining neural networks and Monte Carlo Tree Search (MCTS)—to learn and play Chinese Chess without prior human data. The system includes self-play, training, and evaluation pipelines tailored to Xiangqi's unique game mechanics. -
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ECommerceCrawlers
Collection of Python ecommerce and website crawler examples projects
ECommerceCrawlers is a collection of practical Python web crawler projects designed to gather data from a variety of ecommerce platforms, websites, and online services. It aggregates many independent crawler examples created by contributors and organized into separate subprojects that target specific sites or data sources. These examples demonstrate how to build and operate web scrapers capable of collecting structured information such as product listings, news content, job postings, social media data, and other publicly available web data. ... -
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Girls-In-AI
Free learning code series: Xiaobai's introduction to Python
Girls-In-AI is an educational repository created to encourage women and beginners to learn programming and artificial intelligence through accessible tutorials and practice materials. The project provides a collection of beginner-friendly learning resources covering Python programming, data analysis, machine learning, and deep learning topics. It aims to lower the barrier to entry for people who want to enter the field of artificial intelligence by offering structured learning paths and practical examples. The repository includes Jupyter notebooks, tutorials, and exercises that guide learners through topics such as data processing, machine learning model development, and Kaggle competition practice. ... -
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Elasticquent
Maps Laravel Eloquent models to Elasticsearch types
Elasticsearch for Eloquent Laravel Models. Elasticquent makes working with Elasticsearch and Eloquent models easier by mapping them to Elasticsearch types. You can use the default settings or define how Elasticsearch should index and search your Eloquent models right in the model. Elasticquent uses the official Elasticsearch PHP API. To get started, you should have a basic knowledge of how Elasticsearch works (indexes, types, mappings, etc). When using a database, Eloquent models are... -
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pytorch-examples
Simple examples to introduce PyTorch
The pytorch-examples project is a collection of concise and practical examples demonstrating how to use PyTorch for machine learning and deep learning tasks. It focuses on clarity and minimalism, providing small, self-contained scripts that illustrate key concepts such as neural network training, optimization, and data handling. The examples cover a range of topics including supervised learning, generative models, and reinforcement learning, making it a valuable resource for both beginners and experienced practitioners. ...