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Showing 165 open source projects for "can="
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...This is not a tutorial on how to use your computers. Still here? Awesome! This setup works with a connected PC. You can watch movies and play games with the backglow running. Adds extra ambience to your expeirence. Especially as you transition from bright outdoor scenes to darker indoors ones.
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Eratostene
Show the prime numbers in the form of the Sieve of Eratosthenes
[Versione in italiano sotto] This program can be used to find the prime numbers between 1 and a given number. Also the primes can be visualized in the form of Sieve of Eratosthenes with six columns. The sieve is created in Html and it is possible to save it in a file so that it can be opened with any other browser also after the program was closed. If the browser has the support for JavaScript, it should be possible to show the factorization of a non prime number clicking on it. ... -
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PS-Drone
Programming a Parrot AR.Drone 2.0 with Python - The Easy Way
...The video function is not restricted to mere viewing, it is also possible to analyze video images data using OpenCV2. Obviously, the PS-Drone is perfect for teaching purposes; however, even the requirements for professional purposes can be satisfied. PS-Drone comes with a tutorial, explaining its most important commands and the drone's most important sensor values. The examples are easy to understand for people with little programming experience. A full list of commands and a description of all sensor data is available in a detailed documentation. It took several months to create PS-Drone, so it would be nice to get some donations for further development (e.g. ... -
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Zero Install is a decentralised cross-distribution software installation system. Create one package that works everywhere! With dependency handling and automatic updates, full support for shared libraries, and integration with native package managers
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3d Linear Transformation Visualization
Visualize 3d linear transformations.
A linear transformation is a function from one vector space to another that respects the linear structure of each vector space. For visualizing this we can transform a vector, but it has an obvious problem, because the linear transformation transform the whole space, not just the vector, in other words it transforms the basis vectors thus every vector in the space gets transformed too. That's why i created this app so everyone can see how a transformation matrix change the whole space. -
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interactive-coding-challenges
120+ interactive Python coding interview challenges
...Problems span arrays, strings, stacks, queues, linked lists, trees, graphs, dynamic programming, and more, mirroring common interview themes. Many challenges include hints and reference solutions so you can compare approaches and learn idiomatic patterns. The structure encourages incremental improvement—start with a brute-force idea, then refine to optimal time and space complexity. It serves both as a self-study path and as a warm-up bank for interview prep or coding katas. -
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This project is intended to provide code to be used with MySQL and Python to create a database of major league baseball game events which are freely provided by the mlb.com Gameday application. Older version also support creating a retrosheet.org database but that is no longer supported. All major and minor league pitch location and game statistic data can be downloaded using BBOS. Installation Videos! Part 1: http://youtu.be/rnv2VLcG-eI Part 2: http://youtu.be/eFudbMWHNlQ Special thanks to Wells Oliver for the code for downloading Retrosheet files. And the Chadwick project for its Retrosheet tools. https://sourceforge.net/projects/chadwick/?source=recommended
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Think Bayes
Code repository for Think Bayes
...Instead of heavy focus on continuous mathematics or calculus, the book emphasizes learning Bayesian inference by writing Python programs. The project includes code examples, scripts, and environments that correspond to the chapters of the book. Learners can run the code, experiment with probability distributions, compute posterior probabilities, and understand Bayesian updating via simulation and algorithmic methods. The book and code encourage thinking in terms of discrete approximations (sums over distributions) rather than continuous integrals, making it more accessible to many programmers. ... -
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Python4Proteomics Course
Python course for Proteomics analysis
Python course (in Spanish) for Proteomics analysis using basically Jupyter NoteBooks. For more information, you can have a look at the readme.md file in the source code tree: https://sourceforge.net/p/lp-csic-uab/p4p/code/ci/default/tree/readme.md -
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jieba
Stuttering Chinese word segmentation
...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 for word segmentation in search engines. The paddle mode uses the PaddlePaddle deep learning framework to train the sequence labeling (bidirectional GRU) network model to achieve word segmentation. ... -
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VulnX
Intelligent Bot, Shell can achieve automatic injection
vulnx, an intelligent Bot, Shell can achieve automatic injection, and help researchers detect security vulnerabilities in CMS systems. It can perform a quick CMS security detection, information collection (including sub-domain name, IP address, country information, organizational information and time zone, etc.), and vulnerability scanning. Vulnx is An Intelligent Bot Auto Shell Injector that detects vulnerabilities in multiple types of Cms, fast cms detection, information gathering, and vulnerability scanning of the target like subdomains, IP addresses, country, org, timezone, region, and more. ... -
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Scikit-learn Tutorial
An introductory tutorial for scikit-learn
...It is designed for people who already have a working Python environment and some familiarity with NumPy, SciPy, and Matplotlib. The repository specifies a clear list of dependencies so that participants can reproduce the environment used in the tutorial, and many downstream forks keep the content updated for newer versions of scikit-learn. Although the GitHub repository has been archived and is read-only, it is still a valuable snapshot of early, hands-on teaching material for scikit-learn and machine learning in Python. -
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NiftyNet
An open-source convolutional neural networks platform for research
...NiftyNet is a TensorFlow-based open-source convolutional neural networks (CNNs) platform for research in medical image analysis and image-guided therapy. NiftyNet’s modular structure is designed for sharing networks and pre-trained models. Using this modular structure you can get started with established pre-trained networks using built-in tools. Adapt existing networks to your imaging data. Quickly build new solutions to your own image analysis problems. NiftyNet currently supports medical image segmentation and generative adversarial networks. NiftyNet is not intended for clinical use. -
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Neural MMO
Code for the paper "Neural MMO: A Massively Multiagent Game..."
Neural MMO is a massively multi-agent simulation environment developed by OpenAI for reinforcement learning research. It provides a persistent, procedurally generated world where thousands of agents can interact, compete, and cooperate in real time. The environment is inspired by Massively Multiplayer Online Role-Playing Games (MMORPGs), featuring resource gathering, combat mechanics, exploration, and survival challenges. Agents learn behaviors in a shared ecosystem that supports long-term training and emergent dynamics across large populations. ... -
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Computer Glossary
is a rich dictionary containing multiple computer-related terms
Computer Glossary is a rich dictionary containing multiple computer-related terms, which is useful for both students and professionals. The program integrates an offline database and offers references and descriptions for each term. Computer Glossary can be installed in just a few simple steps and does not require special skills. The program comes with a simple interface and lets you easily search any term. The results will let you see the word's definition, references to other related terms in the dictionary, examples, and the source of the information. -
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If you are looking for the childsplay application please go to http://www.childsplay.mobi
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AngelReader
An E-book, Audio-book, & Library Loader in One Application
...The app can be useful for either classroom or office environment; for personal or commercial use; for general learning or access to practical information. -
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Network Simulator (fork CORE - Live USB)
Live DVD with CORE network simulator
The Common Open Research Emulator (CORE) is a tool for emulating networks on one or more machines. You can connect these emulated networks to live networks. CORE consists of a GUI for drawing topologies of lightweight virtual machines, and Python modules for scripting network emulation. -
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Learn Python the Hard Way
Concise study notes derived from “Learn Python the Hard Way”
This repository contains concise study notes derived from “Learn Python the Hard Way,” organized to reinforce core Python concepts through small, targeted examples. It emphasizes hands-on practice—short scripts, exercises, and explanations that help cement syntax, data structures, functions, and modules. The notes call out common gotchas, idioms, and style preferences so learners form good habits early. Because the content is intentionally compact, it’s easy to revisit a topic quickly when... -
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stanford-tensorflow-tutorials
This repository contains code examples for the Stanford's course
This repository contains code examples for the course CS 20: TensorFlow for Deep Learning Research. It will be updated as the class progresses. Detailed syllabus and lecture notes can be found in the site. For this course, I use python3.6 and TensorFlow 1.4.1. -
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Qutranpy
Interactive electronic quantum transport
Interactive program to perform quantum transport calculations by means of the Landauer and scattering matrix formalism, in a two terminal geometry. The Hamiltonians of leads and scattering region can be modified, adding exchange fields, mass, spin-orbit coupling or superconductivity. -
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PyTorch Book
PyTorch tutorials and fun projects including neural talk
...This part introduces the main modules in PyTorch and some tools commonly used in deep learning. For this part of the content, Jupyter Notebook is used as a teaching tool here, and readers can modify and run with notebooks and repeat experiments. -
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Delta S Plus
A Serious Game prototype for mechanical technicians
...Game Rules: - You use the mouse to move the wrenchs. Click and hold the left mouse button on them and drag them to move them; - Drop the wrenchs on the pump to choose it (in the same way, you can also undo the choice); - After selecting the bomb(s) that you consider the right, press " Enter" (or "Return") on your keyboard to confirm the answer. If the answer is wrong, you lose the game, else, you win; - If the wrenchs touch the pressure vessels, you lose. -
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Acoustic Research Tool (ART)
Acoustic Simulation Library for Frequency and Time Domain Simulations.
...In the time domain generic bidirectional propagation elements, scattering elements, fractional delays, convolution with reflection functions and general z-domain networks are available and can be described using MuParserX expressions. Cylindrical and conical ducts can also be defined based on their geometry. Available models and their parameters can be enumerated and combined to form simulators for complex acoustical structures. Parameters can be specified symbolically by expressions containing other parameter values or global variables. ... -
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Learning to Learn in TensorFlow
Learning to Learn in TensorFlow
Learning to Learn, created by Google DeepMind, is an experimental framework that implements meta-learning—training neural networks to learn optimization strategies themselves rather than relying on manually designed algorithms like Adam or SGD. The repository provides code for training and evaluating learned optimizers that can generalize across different problem types, such as quadratic functions and image classification tasks (MNIST and CIFAR-10). Using TensorFlow, it defines a meta-optimizer model that learns by observing and adapting to the optimization trajectories of other models. The project allows users to compare performance between traditional optimizers and the learned optimizer (L2L) on various benchmarks, demonstrating how optimization strategies can be learned through experience. ...
