Search Results for "algorithm" - Page 4
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Showing 241 open source projects for "algorithm"
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Auth0 for AI Agents now in GAConnect your AI agents to apps and data more securely, give users control over the actions AI agents can perform and the data they can access, and enable human confirmation for critical agent actions.
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Run applications fast and securely in a fully managed environmentRun frontend and backend services, batch jobs, deploy websites and applications, and queue processing workloads without the need to manage infrastructure.
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Reskin Sensor Library
ReSkin Sensor Interfacing Library
...Magnetic sensing separates the electronic circuitry from the passive-interface, making it easier to replace interfaces as they wear out while allowing for a wide variety of form factors. Machine learning allows us to learn sensor response models that are robust to variations across fabrication and time, and our self-supervised learning algorithm enables finer performance enhancement. -
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Crunch
Insane(ly slow but wicked good) PNG image optimization
Crunch is an image compression tool for lossy PNG image file optimization. Using a combination of selective bit depth, color palette reduction and color type, as well as zopfli DEFLATE compression algorithm encoding that employs the pngquant and zopflipng PNG optimization tools, Crunch is effectively able to optimize and compress images with minimal decrease in image quality. While it may produce file size gains larger than those produced by lossless approaches, the impact on image quality is often imperceptible, and optimized file sizes are still significantly lower than the original. -
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Crunch PNG
Insane(ly slow but wicked good) PNG image optimization
Crunch is a tool for lossy PNG image file optimization. It combines selective bit depth, color type, and color palette reduction with zopfli DEFLATE compression algorithm encoding using the pngquant and zopflipng PNG optimization tools. This approach leads to a significant file size gain relative to lossless approaches at the expense of a relatively modest decrease in image quality. Continuous benchmark testing is available in our GitHub Actions CI. Please see the benchmarks directory of this repository for details about the benchmarking approach and instructions on how to execute benchmarks locally on the reference images distributed in this repository or with your own image files. -
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Basic Blind Chess
Blind Chess using Taiwan rule
Blind Chess also known as "Dark Chess" (暗棋) or "Banqi" or Half Chess , is a two-player Chinese board game played on a 4x8 grid, or half of the xiangqi (Chinese Chess) board. This application is using Taiwan rule. AI is using basic minimax tree structure and some rules. Advanced algorithm such as Upper Confidence bounds applied to Trees and Monte Carlo Tree Search are NOT used. This app is single player vs computer only. For English user, Christakis Giorgios made Software Requirements Specification(pdf file), it will help anyone that downloads this application to understand basic blind chess and use it. You can download this pdf in Files->Specification folder. -
D&B Hoovers is Your Sales AcceleratorSpeed up sales prospecting with the rich audience targeting capabilities of D&B Hoovers so you can spend more sales time closing.
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MAGeCK
Model-based Analysis of Genome-wide CRISPR-Cas9 Knockout
Model-based Analysis of Genome-wide CRISPR-Cas9 Knockout (MAGeCK) is a computational tool to identify important genes from the recent genome-scale CRISPR-Cas9 knockout screens technology. For instructions and documentations, please refer to the wiki page. MAGeCK is developed by Wei Li and Han Xu from Dr. Xiaole Shirley Liu's lab at Dana-Farber Cancer Institute/Harvard School of Public Health, and is maintained by Wei Li lab at Children's National Medical Center. We thank the support... -
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qiji-font
Typeface from Ming Dynasty woodblock printed books
...Download high-resolution PDFs and split pages into images. Manually lay a grid on top of each page to generate bounding boxes for characters (potentially replaceable by an automatic corner-detection algorithm). Generate a low-poly mask for each character on the grid, and save the thumbnails (using OpenCV). First, red channel is subtracted from the grayscale, in order to clean the annotations printed in red ink. Next, the image is thresholded and fed into the contour-tracing algorithm. A metric is then used to discard shapes that are unlikely to be part of the character in interest. -
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Machine-Learning
kNN, decision tree, Bayesian, logistic regression, SVM
Machine-Learning is a repository focused on practical machine learning implementations in Python, covering classic algorithms like k-Nearest Neighbors, decision trees, naive Bayes, logistic regression, support vector machines, linear and tree-based regressions, and likely corresponding code examples and documentation. It targets learners or practitioners who want to understand and implement ML algorithms from scratch or via standard libraries, gaining hands-on experience rather than relying... -
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Upscale
This program is upscaling any image by a factor 2 using an algorithm
This program is upscaling any image by a factor 2 using an algorithm of cubic interpolation. You may need to install the following libraries to run the program, tqdm, itertools, and OpenCV. -
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Pokerbot: Pokerstars Partypoker GGPoker
Self playing pokerbot for partypoker, pokerstars and GGPoker
Please visit the wiki page for documentation how to run the bot http://www.github.com/dickreuter/Poker/ This pokerbot plays automatically on Partypoker, Pokerstars and GGPoker. It works with image recognition, montecarlo simulation and a basic genetic algorithm. The mouse is moved automatically and the bot can play for hours. All open source and you are welcome to contribute. New tables can easily be mapped with a new user interface. -
Turn traffic into pipeline and prospects into customersDocket is an AI-powered sales enablement platform designed to unify go-to-market (GTM) data through its proprietary Sales Knowledge Lake™ and activate it with intelligent AI agents. The platform helps marketing teams increase pipeline generation by 15% by engaging website visitors in human-like conversations and qualifying leads. For sales teams, Docket improves seller efficiency by 33% by providing instant product knowledge, retrieving collateral, and creating personalized documents. Built for GTM teams, Docket integrates with over 100 tools across the revenue tech stack and offers enterprise-grade security with SOC 2 Type II, GDPR, and ISO 27001 compliance. Customers report improved win rates, shorter sales cycles, and dramatically reduced response times. Docket’s scalable, accurate, and fast AI agents deliver reliable answers with confidence scores, empowering teams to close deals faster.
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BerryNet
Deep learning gateway on Raspberry Pi and other edge devices
This project turns edge devices such as Raspberry Pi into an intelligent gateway with deep learning running on it. No internet connection is required, everything is done locally on the edge device itself. Further, multiple edge devices can create a distributed AIoT network. At DT42, we believe that bringing deep learning to edge devices is the trend towards the future. It not only saves costs of data transmission and storage but also makes devices able to respond according to the events... -
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Soma-direct
System Omnichannel Marketing Analysis
Soma - System Omnichannel Marketing Analysis is an open-source solution for simplifying the processes of analyzing and predicting consumer behavior. With Soma, you can combine data from multiple systems and channels in the profile joining process. Interactions and behaviors registered as a part of a unique user create and show what a Customer Journey looks like. The data is subjected to an analysis process which enables the examination of the significance of individual touchpoints for the... -
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Zipline
Zipline, a Pythonic algorithmic trading library
Zipline is a Pythonic algorithmic trading library. It is an event-driven system for backtesting. Zipline is currently used in production as the backtesting and live-trading engine powering Quantopian -- a free, community-centered, hosted platform for building and executing trading strategies. Quantopian also offers a fully managed service for professionals that includes Zipline, Alphalens, Pyfolio, FactSet data, and more. Installing Zipline is slightly more involved than the average Python... -
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Pythonic Data Structures and Algorithms
Minimal examples of data structures and algorithms 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. For students preparing for technical interviews, self-learners brushing up on fundamentals, or developers wanting to understand algorithm internals, this repository provides ready-to-run examples, and can serve as a sandbox to experiment, benchmark, or adapt code. Because it’s in pure Python, it’s easy to read and modify, making it accessible even to those with modest programming experience. The repo helps bridge the gap between theoretical algorithm descriptions and real-world code, giving concrete, working implementations that one can study, debug, or extend. -
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levin
in-memory key value server with fuzzy search capabilities
Levin is an event-based key/value server based on radix-tree (space optimized trie). Key search can be performed with an approximate key matching algorithm based on Levenshtein edit distance. -
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DeepCluster
Deep Clustering for Unsupervised Learning of Visual Features
DeepCluster is a classic self-supervised clustering-based representation learning algorithm that iteratively groups image features and uses the cluster assignments as pseudo-labels to train the network. In each round, features produced by the network are clustered (e.g. k-means), and the cluster IDs become supervision targets in the next epoch, encouraging the model to refine its representation to better separate semantic groups. -
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Consistent Depth
We estimate dense, flicker-free, geometrically consistent depth
Consistent Depth is a research project developed by Facebook Research that presents an algorithm for reconstructing dense and geometrically consistent depth information for all pixels in a monocular video. The system builds upon traditional structure-from-motion (SfM) techniques to provide geometric constraints while integrating a convolutional neural network trained for single-image depth estimation. During inference, the model fine-tunes itself to align with the geometric constraints of a specific input video, ensuring stable and realistic depth maps even in less-constrained regions. ... -
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lzhw
LZHW Windows command line lossless compression tool for tabular files
LZHW Command Line Lossless Compression Tool is a Windows command line tool used to compress and decompress files from and to any form, csv, excel etc without any dependencies or installations. Using an optimized algorithm (LZHW) developed from Lempel-Ziv, Huffman and LZ-Welch algorithms. The tool can work in parallel and most of its code is written in Cython, so it is pretty fast. It is based on python lzhw library. Full tool documentation can be found at: https://mnoorfawi.github.io/lzhw/6%20Using%20the%20lzhw%20command%20line%20tool/ While the documentation for the python library is at: https://mnoorfawi.github.io/lzhw/ -
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Forecasting Best Practices
Time Series Forecasting Best Practices & Examples
Time series forecasting is one of the most important topics in data science. Almost every business needs to predict the future in order to make better decisions and allocate resources more effectively. This repository provides examples and best practice guidelines for building forecasting solutions. The goal of this repository is to build a comprehensive set of tools and examples that leverage recent advances in forecasting algorithms to build solutions and operationalize them. Rather than... -
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MADDPG
Code for the MADDPG algorithm from a paper
MADDPG (Multi-Agent Deep Deterministic Policy Gradient) is the official code release from OpenAI’s paper Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments. The repository implements a multi-agent reinforcement learning algorithm that extends DDPG to scenarios where multiple agents interact in shared environments. Each agent has its own policy, but training uses centralized critics conditioned on the observations and actions of all agents, enabling learning in cooperative, competitive, and mixed settings. The code is built on top of TensorFlow and integrates with the Multiagent Particle Environments (MPE) for benchmarking. ... -
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Zat 1.0
Fast N-SAT solver for Windows 10
Zat is an Onagan project. It is a very fast sat solver for .cnf, .dimacs, ... Zat is an O(n^log(n)) time complexity algorithm, which is faster than O((1+e)^n) for e strictly positive. The space complexity is O(n). The version 1.0 is exclusively for Windows 10. -
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jieba
Stuttering Chinese word segmentation
"Jaba" Chinese word segmentation, do the best Python Chinese word segmentation component. Four word segmentation modes are supported. Precise mode, which tries to cut the sentence most precisely, suitable for text analysis. Full mode, scans all the words that can be formed into words in the sentence, the speed is very fast, but the ambiguity cannot be resolved. The search engine mode, on the basis of the precise mode, divides the long words again to improve the recall rate, which is suitable... -
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deep-q-learning
Minimal Deep Q Learning (DQN & DDQN) implementations in Keras
The deep-q-learning repository authored by keon provides a Python-based implementation of the Deep Q-Learning algorithm — a cornerstone method in reinforcement learning. It implements the core logic needed to train an agent using Q-learning with neural networks (i.e. approximating Q-values via deep nets), setting up environment interaction loops, experience replay, network updates, and policy behavior. For learners and researchers interested in reinforcement learning, this repo offers a concrete, runnable example bridging theory and practice: you can execute the code, play with hyperparameters, observe convergence behavior, and see how deep Q-learning learns policies over time in standard environments. ... -
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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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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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Coach
Enables easy experimentation with state of the art algorithms
Coach is a python framework that models the interaction between an agent and an environment in a modular way. With Coach, it is possible to model an agent by combining various building blocks, and training the agent on multiple environments. The available environments allow testing the agent in different fields such as robotics, autonomous driving, games and more. It exposes a set of easy-to-use APIs for experimenting with new RL algorithms and allows simple integration of new environments...
