Search Results for "learning classifier system" - Page 5
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Showing 199 open source projects for "learning classifier system"
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Linux-Tutorial
Learning repository written from the perspective of a Java programmer
...The author presents it as a personal knowledge organization project rather than a perfectly formal manual, encouraging readers to approach it critically. It is most useful for Java developers, backend learners, and system beginners who want practical Linux operation knowledge. -
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Detectron2
Next-generation platform for object detection and segmentation
Detectron2 is Facebook AI Research's next generation software system that implements state-of-the-art object detection algorithms. It is a ground-up rewrite of the previous version, Detectron, and it originates from maskrcnn-benchmark. It is powered by the PyTorch deep learning framework. Includes more features such as panoptic segmentation, Densepose, Cascade R-CNN, rotated bounding boxes, PointRend, DeepLab, etc. -
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ESP8266 Deauther Version 2
Affordable WiFi hacking platform for testing and learning
Scan for WiFi devices, block selected connections, create dozens of networks and confuse WiFi scanners! Version 3 is in development. It is stable to use, but it is very different. It is command-line based, which allows it to offer not just more features, but make them more customizable. This software allows you to easily perform a variety of actions to test 802.11 wireless networks by using an inexpensive ESP8266 WiFi SoC (System On A Chip). The main feature, the deauthentication attack, is... -
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rax
A progressive React framework for building universal application
Ultra-lightweight, high-performance, easy-to-use front-end solution. One-time development and multi-terminal operation, liberating repetitive work, focusing on product logic, and improving development efficiency. The Rax 1.0 system provides a wealth of components and APIs to help business students quickly develop multi-terminal projects. Go Rax is a Rax 1.0 sample app, which is provided for Rax developers for reference and learning. Rax improves the product experience through a lighter core, progressive web applications, and server-side rendering. The out-of-the-box engineering, rich components and surrounding ecology, and one-time development and multi-end delivery help the developer complete his creativity. ... -
Host LLMs in Production With On-Demand GPUsDeploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
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libpython-clj
Python bindings for Clojure
libpython-clj is a deep interop library enabling you to load and use Python modules from within Clojure as if they were native namespaces—and even extend Python objects from Clojure. It bridges to the Python C API, preserving REPL‑based workflows. Bridge between JVM objects and Python objects easily; use Python in your Java and use some Java in your Python. Python objects are linked to the JVM GC such that when they are no longer reachable from the JVM, their references are released.... -
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workshops_project
Workshops is an open source, simple, dead-lightweight LMS
Workshops is an open source, simple, dead-lightweight LMS (Learning Management System) application programmed in Python (version 3.8.x) with Django (version 2.2.x) web framework which main purpose is to make a standarized way to share knowledge via courses in a slide-based view in browser powered by remark javascript library, easy to create, edit, delete and show your courses using simple markdown and html if necessary. -
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raspberry-pi-os
Learning operating system development using Linux kernel and Raspberry
This project provides a step-by-step educational guide on building a simple operating system kernel entirely from scratch, specifically targeting the Raspberry Pi 3. The operating system, referred to as RPi OS, is inspired by the Linux kernel but remains intentionally minimal to focus on clarity and teaching fundamental OS concepts. Each lesson introduces a kernel feature and demonstrates its implementation within RPi OS, followed by a comparison to how the same concept is realized in the Linux kernel. ... -
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MIT-6.824
Basic Sources for MIT 6.824 Distributed Systems Class
MIT-6.824 is a study repository containing source code and supporting material for MIT's distributed systems course. Its materials are based on the 2021 version of the class and organize resources around lectures and practical exercises. Topics include MapReduce, remote procedure calls, threads, the Google File System, primary-backup replication, and Raft consensus. The repository includes Go-based exercises such as crawler, key-value, and MapReduce labs. It also collects lecture questions... -
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YOLO ROS
YOLO ROS: Real-Time Object Detection for ROS
This is a ROS package developed for object detection in camera images. You only look once (YOLO) is a state-of-the-art, real-time object detection system. In the following ROS package, you are able to use YOLO (V3) on GPU and CPU. The pre-trained model of the convolutional neural network is able to detect pre-trained classes including the data set from VOC and COCO, or you can also create a network with your own detection objects. The YOLO packages have been tested under ROS Noetic and... -
Build Data Resilience - Take the Assessment TodayIs your recovery strategy as strong as you think? Take this quick self-assessment to check your recovery readiness and gain tailored insights. In only 2 minutes, you'll learn where you fall on the recovery readiness scale.
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PyTorch SimCLR
PyTorch implementation of SimCLR: A Simple Framework
...In situations like this, we take the models’ pre-trained weights, append a new classifier layer on top of it, and retrain the network. This is called transfer learning, and is one of the most used techniques in CV. Aside from a few tricks when performing fine-tuning (if the case), it has been shown (many times) that if training for a new task, models initialized with pre-trained weights tend to learn faster and be more accurate then training from scratch using random initialization. -
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gradslam
gradslam is an open source differentiable dense SLAM library
...Leveraging the automatic differentiation capabilities of computational graphs, gradSLAM enables the design of SLAM systems that allow for gradient-based learning across each of their components, or the system as a whole. -
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OpenPose
Real-time multi-person keypoint detection library for body, face, etc.
OpenPose has represented the first real-time multi-person system to jointly detect human body, hand, facial, and foot keypoints (in total 135 keypoints) on single images. It is authored by Ginés Hidalgo, Zhe Cao, Tomas Simon, Shih-En Wei, Yaadhav Raaj, Hanbyul Joo, and Yaser Sheikh. It is maintained by Ginés Hidalgo and Yaadhav Raaj. OpenPose would not be possible without the CMU Panoptic Studio dataset. We would also like to thank all the people who has helped OpenPose in any way. 15, 18 or... -
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CYBR-SUITE
Remote Scrum Communication & Collaboration Suite :: Scrum Board & co
...Personality assessments, ...these mandatory ways to add more context & breaking-down complexity enable a better overview and a better understanding - for man and machine... ...based on the standardized structure of the DATA WE ARE NOW CREATING AND STORING, these values can now be used directly for the inputs and targets of our artificial neuronal networks and generate our competitive advantage based on SUPERIOR MACHINE LEARNING capabilities. The CYSU is a docker-compose solution: 1. prepare your Linux system with docker & docker-compose, modify the init-script & set YOUR SSL-values, chmod +x 2. docker-compose up --build Follow the detailed step-by-step documentation. >>> PS: YOU NEED A LINUX SERVER FOR INSTALL IT ! <<< -
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pico
A Git-driven task runner built to facilitate GitOps and Infrastructure
...What once was a place to chat and collaborate with people across the planet is now a platform for the commercialization of products and services. At the seat of the modern web is the browser. The modern browser is very much like an operating system, both in terms of complexity and code size. Only massive corporations can build and maintain it. Further, the web breeds platforms that exploit your reward and learning centers in order to increase "engagement." We have no issue with the commercialization of the web -- that's how useful services exist. However, we are more aligned with products and services that promote human communication and collaboration in its purest forms. ... -
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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... -
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Kore
Scalable and secure web application framework
Kore is a web application platform for writing scalable, concurrent web-based processes in C or Python. It is built with a "secure by default" approach. It is fully privileged separated while using strong security features at the operating system level such as second, pledge, unveil, and more. Today Kore is used in a variety of applications ranging from high assurance cryptographic military devices, machine-learning stacks and even in the aerospace industry. From embedded platforms all the way to high-performance servers. Kore scales. Kore is open source software licensed under the ISC license and developed in my spare time. ... -
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Euler
A distributed graph deep learning framework.
As a general data structure with strong expressive ability, graphs can be used to describe many problems in the real world, such as user networks in social scenarios, user and commodity networks in e-commerce scenarios, communication networks in telecom scenarios, and transaction networks in financial scenarios. and drug molecule networks in medical scenarios, etc. Data in the fields of text, speech, and images is easier to process into a grid-like type of Euclidean space, which is suitable for processing by existing deep learning models. Graph is a data type in non-Euclidean space and cannot be directly applied to existing methods, requiring a specially designed graph neural network system. Graph-based learning methods such as graph neural networks combine end-to-end learning with inductive reasoning, and are expected to solve a series of problems such as relational reasoning and interpretability that deep learning cannot handle. -
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Albedo
A recommender system for discovering GitHub repos
Albedo is an open-source recommender system aimed at helping developers discover GitHub repositories by learning from activity signals. It treats repositories and developers as a graph of interactions and applies large-scale matrix factorization to model affinities, with Apache Spark providing the distributed data processing. The project focuses on implicit feedback—stars, watches, and other engagement metrics—so it can build useful recommendations without explicit ratings. ... -
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TensorFlow Object Counting API
The TensorFlow Object Counting API is an open source framework
...Please contact if you need professional object detection & tracking & counting project with super high accuracy and reliability! You can train TensorFlow models with your own training data to built your own custom object counter system! If you want to learn how to do it, please check one of the sample projects, which cover some of the theory of transfer learning and show how to apply it in useful projects. The development is on progress! The API will be updated soon, the more talented and light-weight API will be available in this repo! Detailed API documentation and sample jupyter notebooks that explain basic usages of API will be added! -
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threadandjuc
High performance three-high-import import system
threadandjuc is a Java learning repository focused on multithreading, concurrency, and JUC concepts. It is designed to help developers understand how Java concurrent programming works through examples, explanations, and practical project-style demonstrations. The project covers topics such as threads, locks, synchronization, thread pools, concurrent collections, and high-performance data handling. It is especially useful for Java developers preparing for interviews or improving their... -
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12306 Ticket Buying Assistant
12306 Smart ticket swiping, ticket booking
...The system is particularly useful during peak travel periods when tickets sell out quickly, as it can continuously monitor availability and attempt purchases automatically. It includes support for account management, login handling, and CAPTCHA-solving integrations to mimic real user behavior. The project is often used as both a practical utility and a learning resource for understanding HTTP automation and web interaction. -
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X11workbench
X11 developer's 'workbench' and lightweight toolkit API
(preliminary) X11 developer's 'workbench' application using a lightweight statically linked custom toolkit that is intended to be used by X11 applications built with the X11 Workbench. The primary goal of the toolkit is ease of use (short learning curve), lightweight self-contained executables, UI speed, cross platform compatibility, and minimal dependencies. The primary goal of the workbench is to provide an editor on X11 platforms that integrates development, provides rapid development... -
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abu
Abu quantitative trading system (stocks, options, futures, bitcoin)
Abu Quantitative Integrated AI Big Data System, K-Line Pattern System, Classic Indicator System, Trend Analysis System, Time Series Dimension System, Statistical Probability System, and Traditional Moving Average System conduct in-depth quantitative analysis of investment varieties, completely crossing the user's complex code quantification stage, more suitable for ordinary people to use, towards the era of vectorization 2.0. The above system combines hundreds of seed quantitative models,... -
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Active Learning
Framework and examples for active learning with machine learning model
Active Learning is a Python-based research framework developed by Google for experimenting with and benchmarking various active learning algorithms. It provides modular tools for running reproducible experiments across different datasets, sampling strategies, and machine learning models. The system allows researchers to study how models can improve labeling efficiency by selectively querying the most informative data points rather than relying on uniformly sampled training sets. ... -
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Facets
Visualizations for machine learning datasets
The power of machine learning comes from its ability to learn patterns from large amounts of data. Understanding your data is critical to building a powerful machine learning system. Facets contains two robust visualizations to aid in understanding and analyzing machine learning datasets. Get a sense of the shape of each feature of your dataset using Facets Overview, or explore individual observations using Facets Dive.
