Search Results for "data structure" - Page 5
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Showing 180 open source projects for "data structure"
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Securden Privileged Account ManagerDiscover and manage administrator, service, and web app passwords, keys, and identities. Automate management with approval workflows. Centrally control, audit, monitor, and record all access to critical IT assets.
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ArkID
Enterprise IDaaS/IAM platform system
...You can flexibly and quickly add new functions to the main program without changing the main program. Achieve centralized and safe storage of corporate organizational structure and identity information of massive personnel. Establish a correspondence in multiple dimensions and securely integrate enterprise identity data sources. To achieve efficient and unified management of enterprise personnel, organizational structure, and application of information on a platform. -
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Jraph
A Graph Neural Network Library in Jax
Jraph (pronounced “giraffe”) is a lightweight JAX library developed by Google DeepMind for building and experimenting with graph neural networks (GNNs). It provides an efficient and flexible framework for representing, manipulating, and training models on graph-structured data. The core of Jraph is the GraphsTuple data structure, which enables users to define graphs with arbitrary node, edge, and global attributes, and to batch variable-sized graphs efficiently for JAX’s just-in-time compilation. The library includes a comprehensive set of utilities for batching, padding, masking, and partitioning graph data, making it ideal for distributed and large-scale GNN experiments. ... -
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AI Chatbots based on GPT Architecture
Training & Implementation of chatbots leveraging GPT-like architecture
...It sure seems like there are a lot of text-generation chatbots out there, but it's hard to find a python package or model that is easy to tune around a simple text file of message data. This repo is a simple attempt to help solve that problem. ai-msgbot covers the practical use case of building a chatbot that sounds like you (or some dataset/persona you choose) by training a text-generation model to generate conversation in a consistent structure. This structure is then leveraged to deploy a chatbot that is a "free-form" model that consistently replies like a human. ... -
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MAE (Masked Autoencoders)
PyTorch implementation of MAE
MAE (Masked Autoencoders) is a self-supervised learning framework for visual representation learning using masked image modeling. It trains a Vision Transformer (ViT) by randomly masking a high percentage of image patches (typically 75%) and reconstructing the missing content from the remaining visible patches. This forces the model to learn semantic structure and global context without supervision. The encoder processes only the visible patches, while a lightweight decoder reconstructs the... -
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GANformer
Generative Adversarial Transformers
This is an implementation of the GANformer model, a novel and efficient type of transformer, explored for the task of image generation. The network employs a bipartite structure that enables long-range interactions across the image, while maintaining computation of linearly efficiency, that can readily scale to high-resolution synthesis. The model iteratively propagates information from a set of latent variables to the evolving visual features and vice versa, to support the refinement of... -
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Easy Upscale
A simple image upscaler application using EDSR, ESPCN, FSRCNN, etc.
This application was made to fulfill the assignment for the Data Structures course. The concept of the application is an application to upgrade/enhance image quality. The main theme is queues, we implement circular queues for pooling/storing a list of images to be upscaled. Gui creation is made manually using the tkinter library. For the upscale process itself, it uses the OpenCV library with a model obtained from open source. Checked using vermin. Minimum required versions: 3.6 Incompatible... -
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tensorflow_template_application
TensorFlow template application for deep learning
tensorflow_template_application is a template project that demonstrates how to structure scalable applications built with TensorFlow. The repository provides a standardized architecture that helps developers organize machine learning code into clear components such as data processing, model training, evaluation, and deployment. Instead of focusing on a specific algorithm, the project emphasizes software engineering practices that make machine learning systems easier to maintain and extend. ... -
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Data Science Notes
Curated collection of data science learning materials
Data Science Notes is a large, curated collection of data science learning materials, with explanations, code snippets, and structured notes across the typical end-to-end workflow. It spans foundational math and statistics through data wrangling, visualization, machine learning, and practical project organization. The content emphasizes hands-on understanding by pairing narrative notes with runnable examples, making it useful for both self-study and classroom settings. Because it aggregates... -
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Semantic Segmentation in PyTorch
Semantic segmentation models, datasets & losses implemented in PyTorch
Semantic segmentation models, datasets and losses implemented in PyTorch. PyTorch and Torchvision needs to be installed before running the scripts, together with PIL and opencv for data-preprocessing and tqdm for showing the training progress. PyTorch v1.1 is supported (using the new supported tensoboard); can work with earlier versions, but instead of using tensoboard, use tensoboardX. Poly learning rate, where the learning rate is scaled down linearly from the starting value down to zero... -
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ipfs-api-mount
Mount IPFS directory as local FS
Mount IPFS directory as local FS. go-ipfs daemon has this function but as of version 0.9.1 it's slow. ipfs-api-mount aims to be more efficient. For sequential access to random data it's ~3 times slower than ipfs cat but also ~20 times faster than cating files mounted by go-ipfs. It's supposed that FS mounted by go-ipfs daemon is slow because of file structure being accessed in every read. By adding caching one can improve performance a lot. Apart from mounting one specified CID you can also mount whole IPFS namespace. ... -
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BeaEngine 5
BeaEngine disasm project
BeaEngine is a C library designed to decode instructions from 16-bit, 32-bit and 64-bit intel architectures. It includes standard instructions set and instructions set from FPU, MMX, SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2, VMX, CLMUL, AES, MPX, AVX, AVX2, AVX512 (VEX & EVEX prefixes), CET, BMI1, BMI2, SGX, UINTR, KL, TDX and AMX extensions. If you want to analyze malicious codes and more generally obfuscated codes, BeaEngine sends back a complex structure that describes precisely the... -
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Image GPT
Large-scale autoregressive pixel model for image generation by OpenAI
...While the repository is archived and provided as-is, it remains a valuable starting point for experimenting with autoregressive transformers applied directly to raw pixel data. By demonstrating GPT’s flexibility across modalities, Image-GPT influenced subsequent multimodal generative research. -
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Tensorflow 2017 Tutorials
Tensorflow tutorial from basic to hard
Tensorflow 2017 Tutorials is a structured set of tutorials that introduce developers to TensorFlow, starting with basic neural network constructs and progressing to sophisticated model architectures and training techniques. This repository covers essential building blocks like sessions (for older TF versions), placeholders, variables, activation functions, and optimizers, before guiding learners through building end-to-end models for regression, classification, and data pipelines. Beyond the... -
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TimothyDocs
Timothy is a cloud base storage system designed to document your work
...Like most storge schemes timothy creates a hierarchy of categories through which one may browse. Timothy displays information about the document or category as well as its name. This use of meta data explains the structure and content of the project to the user as he browses. Users make better informed decisions about where to file a document when this information is available to them. It also suggests where to look for a long lost document. -
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Tofu
Tofu is a Python tool for generating synthetic UK Biobank data
...Tofu will generate synthetic data which conforms to the structure of the baseline data UK Biobank sends researchers by generating random values. For categorical variables (single or multiple choices), a random value will be picked from the UK Biobank data dictionary for that field. For continuous variables, a random value will be generated based on the distribution of values reported for that field on the UK Biobank showcase. -
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interactive-coding-challenges
120+ interactive Python coding interview challenges
...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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BlackWidow
Python web scanner for OSINT gathering and OWASP vulnerability fuzzing
...It functions as a web spider that systematically explores a site to gather valuable information such as URLs, dynamic parameters, subdomains, email addresses, and phone numbers associated with the target domain. By automatically extracting this data, BlackWidow helps security professionals and researchers build a clearer understanding of a website’s structure and publicly accessible information. In addition to information gathering, the project includes a built-in fuzzing component called Inject-X, which tests dynamic URLs for common vulnerabilities listed in the OWASP Top 10. ... -
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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. A reproducible... -
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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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CrypTen
A framework for Privacy Preserving Machine Learning
CrypTen is a research framework developed by Facebook Research for privacy-preserving machine learning built directly on top of PyTorch. It provides a secure and intuitive environment for performing computations on encrypted data using Secure Multiparty Computation (SMPC). Designed to make secure computation accessible to machine learning practitioners, CrypTen introduces a CrypTensor object that behaves like a regular PyTorch tensor, allowing users to seamlessly apply automatic differentiation and neural network operations. Its design mirrors PyTorch’s modular and library-based structure, enabling flexible experimentation, debugging, and model development. ... -
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Backuso
Backup software for your data to local and remote SSH systems
Backuso – pronounce like the opera singer ‘Caruso’ – is a software for routine and automated backups of your computer to either a local storage or a remote storage on an SSH server, or both. A local storage is anything accessible in the directory structure of your computer. Most of the time this will be a (large) hard drive, mounted at a convenient location. A remote storage is anything which is accessed on your network via the ssh protocol. This could be a NAS (Network Attached... -
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TensorFlow Machine Learning Cookbook
Code for Tensorflow Machine Learning Cookbook
TensorFlow Machine Learning Cookbook repository provides practical code examples and educational materials that accompany the book TensorFlow Machine Learning Cookbook. The repository contains numerous Python scripts and Jupyter notebooks that demonstrate how to implement machine learning algorithms and neural networks using the TensorFlow framework. Each section focuses on a different aspect of machine learning development, including tensor manipulation, model training, optimization... -
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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. ... -
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yapydata
Lower-Layer unified data - JSON, XML, YAML + INI, CFG, properties
The yapydata - Yet Another Python Data - provides a unified interface for the access to various data syntaxes. Therefore it encapsulates the libraries by offering a common API with the canonical internal data as JSON compatible Python in-memory structure. The application is foreseen in particular for the lower layer of the software stack including setup-tools. Thus it uses standard libraries only whenever possible. -
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Olex2 is visualisation software for small-molecule crystallography developed at Durham University/EPSRC. It provides comprehensive tools for crystallographic model manipulation for the end user and an extensible development framework for programmers. The project has been supported by Olexsys Ltd since 2010.
