Search Results for "project-open" - Page 6
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Showing 687 open source projects for "project-open"
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Python/FEniCS Examples
phase-field simulation and other examples with Python/FEniCS
The main goal of this project was developing phase-field simulations of lithium dendrite growth with FEniCS programmed in Python. The problem was based in the grand potential-based model of Zijian Hong and Venkatasubramanian Viswanathan (https://doi.org/10.1021/acsenergylett.8b01009) . Some simpler examples were developed before for a first approach with FEniCS: heat equation and combustion model. -
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IPython
Command shell for interactive computing in multiple languages
IPython provides a rich toolkit to help you make the most of using Python interactively. Comprehensive object introspection. IPython provides input history, persistent across sessions. Caching of output results during a session with automatically generated references. Extensible tab completion, with support by default for completion of python variables and keywords, filenames and function keywords. Extensible system of ‘magic’ commands for controlling the environment and performing many... -
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The Player Project: Player is a networked interface to robots and sensors. Stage and Gazebo are Player-friendly multiple-robot simulators. The software aims for POSIX compliance and runs on most UNIX-like OS's. Some parts also work on Windows.
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interactive-coding-challenges
120+ interactive Python coding interview challenges
Interactive Coding Challenges is a collection of practice problems designed to strengthen data structures, algorithms, and problem-solving skills. The repository emphasizes a learn-by-doing approach: you read a prompt, attempt a solution, and verify behavior with tests, often within notebooks or scripts. Problems span arrays, strings, stacks, queues, linked lists, trees, graphs, dynamic programming, and more, mirroring common interview themes. Many challenges include hints and reference... -
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pytorch-tutorial
PyTorch Tutorial for Deep Learning Researchers
...Each section includes runnable code examples that progressively increase in complexity, helping learners build intuition while practicing hands-on implementation. Because the tutorials are concise and practical, the project is widely used in classrooms and self-study environments. Overall, it functions as both a learning curriculum and a quick reference for common PyTorch workflows. -
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...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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Tensorflow and deep learning
A crash course in six episodes for software developers
Tensorflow and deep learning repository is an educational deep learning crash course designed to help software developers quickly understand and apply machine learning concepts without requiring advanced academic background. It is structured as a series of guided lessons that combine theoretical explanations, practical examples, and runnable code, allowing learners to build intuition while actively experimenting with models. The repository covers core neural network concepts such as weights,... -
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PyTorch GAN Zoo
A mix of GAN implementations including progressive growing
PyTorch GAN Zoo is a comprehensive open research toolbox designed for experimenting with and developing Generative Adversarial Networks (GANs) using PyTorch. The project provides modular implementations of popular GAN architectures, including Progressive Growing of GANs (PGAN), DCGAN, and an experimental StyleGAN version. It is built to support both researchers and developers who want to train, evaluate, and extend GANs efficiently across diverse datasets such as CelebA-HQ, FashionGen, DTD, and CIFAR-10. ... -
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Think Bayes
Code repository for Think Bayes
ThinkBayes is the code repository accompanying Think Bayes: a book on Bayesian statistics written in a computational style. 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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BPF Performance Tools
Official repository for the BPF Performance Tools book
...The repository showcases how eBPF enables safe, low-overhead tracing directly inside the Linux kernel without requiring intrusive instrumentation. It includes tools for profiling, latency analysis, syscall tracing, and troubleshooting distributed systems or production environments. Overall, the project is regarded as a foundational resource for understanding advanced Linux performance engineering and observability techniques. -
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DeepLearning
Deep Learning (Flower Book) mathematical derivation
" Deep Learning " is the only comprehensive book in the field of deep learning. The full name is also called the Deep Learning AI Bible (Deep Learning) . It is edited by three world-renowned experts, Ian Goodfellow, Yoshua Bengio, and Aaron Courville. Includes linear algebra, probability theory, information theory, numerical optimization, and related content in machine learning. At the same time, it also introduces deep learning techniques used by practitioners in the industry, including... -
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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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GoodByeCatpcha
Solver ReCaptcha v2 Free
An async Python library to automate solving ReCAPTCHA v2 by images/audio using Mozilla's DeepSpeech, PocketSphinx, Microsoft Azure’s, Google Speech and Amazon's Transcribe Speech-to-Text API. Also image recognition to detect the object suggested in the captcha. Built with Pyppeteer for Chrome automation framework and similarities to Puppeteer, PyDub for easily converting MP3 files into WAV, aiohttp for async minimalistic web-server, and Python’s built-in AsyncIO for convenience. -
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StepIntoChinese
Chinese language tool
Explore Chinese. Application uses data structure with over 26,000 words/concepts and 8,300 characters. -
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Tux Math Scrabble
12÷16×3=9÷4
Latest version 0.9.1 runs on Python3. Date: June 15, 2023 Online/touch-screen version: https://www.asymptopia.com/tuxmathscrabble/ Encourages kids to construct compound equations and consider multiple abstract possibilities. -
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Spinning Up in Deep RL
Educational resource to help anyone learn deep reinforcement learning
Welcome to Spinning Up in Deep RL! This is an educational resource produced by OpenAI that makes it easier to learn about deep reinforcement learning (deep RL). For the unfamiliar, reinforcement learning (RL) is a machine learning approach for teaching agents how to solve tasks by trial and error. Deep RL refers to the combination of RL with deep learning. At OpenAI, we believe that deep learning generally, and deep reinforcement learning specifically, will play central roles in the... -
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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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Web Security Dojo
Virtual training environment to learn web app ethical hacking.
Web Security Dojo is a virtual machine that provides the tools, targets, and documentation to learn and practice web application security testing. A preconfigured, stand-alone training environment ideal for classroom and conferences. No Internet required to use. Ideal for those interested in getting hands-on practice for ethical hacking, penetration testing, bug bounties, and capture the flag (CTF). A single OVA file will import into VirtualBox and VMware. There is also an Ansible... -
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A Machine Learning Course with Python
A course about machine learning with Python
...In this project, we built our tutorials using many different well-known Machine Learning frameworks such as Scikit-learn. In this project you will learn what is the definition of Machine Learning? When it started and what is the trending evolution? What are the Machine Learning categories and subcategories? What are the mostly used Machine Learning algorithms and how to implement them? -
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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... -
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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... -
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NiftyNet
An open-source convolutional neural networks platform for research
An open-source convolutional neural networks platform for medical image analysis and image-guided therapy. 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. -
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Neural MMO
Code for the paper "Neural MMO: A Massively Multiagent Game..."
...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. The project is built to test scalability in multi-agent reinforcement learning, with features such as procedurally generated terrain and configurable game mechanics. While the original release has since been succeeded by newer versions maintained outside OpenAI, it remains a landmark framework for studying large-scale agent interactions in complex environments. -
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Pydicom by examples
Basic and intermediate examples of DICOM library with Jupyter
Basic and intermediate examples to read, modify and write DICOM files with Python code using Jupyter - To install Jupyter - https://jupyter.org/install ====== All examples are based on Pydicom. An open source library - https://pydicom.github.io/ -
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A symbolic framework for C++, Python and Octave implementing automatic differentiation by source code transformation in forward and reverse modes on sparse matrix-valued computational graphs.