Search Results for "malware-samples" - Page 11
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Showing 847 open source projects for "malware-samples"
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metatea
METATEA enables fast 16S rRNA-based analyses at the sequence level
○ METATEA is developed to support 16S rRNA-based analyses at sequence level using both sequence-supervised and unsupervised modes for rapid and accurate comparison across samples and groups. ○ The sequence-supervised approaches using bacterial sequences from healthy persons and IBD patients were developed. However, you should use the same primers and sequencing platform for the sequence-supervised approaches. ○ Exclusive correlation value (ECV) was defined for the detection of mutually exclusive relationships between bacteria like probiotics and pathogens that are antagonistic each other. ... -
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Amazon SageMaker Operators Kubernetes
Amazon SageMaker operator for Kubernetes
Amazon SageMaker is a fully managed machine learning service. With SageMaker, data scientists and developers can quickly and easily build and train machine learning models, and then directly deploy them into a production-ready hosted environment. It provides an integrated Jupyter authoring notebook instance for easy access to your data sources for exploration and analysis, so you don't have to manage servers. It also provides common machine learning algorithms that are optimized to run... -
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PoreMeth
PoreMeth is a tool for the identification of DMRs from Nanopore data.
PoreMeth is a tool for the detection of differentially methylated regions (DMRs) from nanopore sequencing data of two samples. PoreMeth tool is based on a heterogeneous form of the shifting level model, which integrates distances between consecutive CpGs in the segmentation algorithm. PoreMeth is fed with ∆β values and generates genomic segments with increased (hyper-) or decreased (hypo-) methylation levels between two samples, which are then evaluated for statistical significance using the Wilcoxon-rank sum test. -
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Hello AI World
Guide to deploying deep-learning inference networks
...You’ll also get to code your own easy-to-follow recognition program in Python or C++, and train your own DNN models onboard Jetson with PyTorch. Ready to dive into deep learning? It only takes two days. We’ll provide you with all the tools you need, including easy to follow guides, software samples such as TensorRT code, and even pre-trained network models including ImageNet and DetectNet examples. Follow these directions to integrate deep learning into your platform of choice and quickly develop a proof-of-concept design. -
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Reskin Sensor Library
ReSkin Sensor Interfacing Library
...However, the same properties of conformal contact result in faster deterioration of soft sensors and larger variations in their response characteristics over time and across samples, inhibiting their ability to be long-lasting and replaceable. ReSkin is a tactile soft sensor that leverages machine learning and magnetic sensing to offer a low-cost, diverse and compact solution for long-term use. 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. ... -
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Guided Diffusion
Codebase for Diffusion Models Beat GANS on Image Synthesis
...A key insight is that combining diffusion sampling with classifier gradients allows fine control over the generated images, trading off diversity vs fidelity. The repository includes scripts such as image_train.py, image_sample.py, and classifier_train.py to train diffusion models, generate samples, and train guiding classifiers. It also ships with precomputed evaluation batches and baseline comparisons to support reproducible benchmarking of new models. -
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Data Analysis for the Life Sciences
Rmd source files for the HarvardX series PH525x
...It functions as the canonical source for course lab exercises, lecture modules, and reading materials in reproducible format. Students and learners use these R Markdown files to follow along, knit notebooks, run code samples, and complete the lab-based assignments. The repo is licensed under MIT, allowing reuse and modification. It is part of a larger ecosystem: the compiled HTML / book version of the labs is published via a companion “book” repository, which presents a polished, browsable version of the materials. The content covers topics such as data wrangling in R, statistical inference, genomics workflows, Bioconductor packages, and project-based analyses. ... -
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Please use these scripts with care. I hold no accountability if these scripts harm your machine, you have been warned.
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Flame Auto Clicker
Fastest Auto Clicker on the market . Over 1000 CPS (For Real)
Flame Auto Clicker is an Open Source minimalist Auto Clicker. The CPS limit is your PC, but you can also add delay or click limit, or change the click button or start/stop clicking with a HotKey, which can be edited too. This Auto Clicker can be used with ANY game, Minecraft, Roblox and more! Source Code: GitHub: https://github.com/PETEROLO291/Flame-Auto-Clicker TIP: Set delay to 0 to get super fast clicks. Clicks are only limited by your PC hardwere! Installer: 9,22... -
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mlscraper
ML-based HTML scraper that learns extraction rules from examples
...Internally, the project processes HTML documents, identifies relevant elements in the DOM, and builds extraction logic based on statistical or heuristic analysis of the training samples. The result is a developer-oriented tool that aims to automate common scraping workflows. -
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the-way-to-go_ZH_CN
The Chinese translation of "The Way to Go" Guide
the-way-to-go_ZH_CN is the Chinese translation of the Go programming book The Way to Go, known as (“Go Introduction Guide”). The translator, along with a team of contributors, created this project to make a high-quality Go learning resource accessible to Chinese readers who might struggle with English-language books. The README explains that the original author, Ivo Balbaert, granted authorization for the translation and even for updating certain content to match newer Go versions. The... -
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sRNAWorkbench
The UEA sRNA Workbench
A suite of tools for analysing small RNA (sRNA) data from Next Generation Sequencing devices. Including expression profiling of known mirco RNA (miRNA), identification of novel miRNA in deep-sequencing data and identification of other interesting landmarks within high-throughput genetic data -
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Catppuccin
Soothing pastel theme for the high-spirited
...It consists of 4 soothing warm flavors with 26 eye-candy colors each, perfect for coding, designing, and much more! In addition, this repository tracks the development of the actual color palette, the project's documentation, organization-wide assets, resources and code samples for maintainers/developers. -
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SpringBoot Labs
A repository covering six columns
...The repository is designed for developers who already understand the basics of Spring Boot and want to expand their skills into more complex and modern use cases. Through detailed code samples and explanations, it serves as both an educational and practical toolkit for mastering Spring Boot & related frameworks. -
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Google Cloud Vision API examples
Sample code for Google Cloud Vision
The cloud-vision repository is a sample code collection for the Google Cloud Vision API that shows developers how to implement image analysis tasks across a wide range of languages and platforms. It contains examples organized by language and environment, including Go, Java, Node.js, PHP, Python, Ruby, .NET, Android, iOS, and even a Chrome extension, which makes it especially valuable as a cross-platform learning resource. The repository demonstrates concrete image understanding use cases,... -
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Fusion Detection Pipeline
Fusion gene detection pipeline bundled into a Singularity container.
...Further filtering is realized by a custom blacklist, our Promiscuity Score (PS) and Robustness Score (RS). Identified fusion genes are reported with evidence levels based on our filtering. This pipeline has been developed and optimized in a study of 806 AML patient samples (https://doi.org/10.3324/haematol.2021.278436). -
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Fashion-MNIST
A MNIST-like fashion product database
Fashion-MNIST is an open-source dataset created by Zalando Research that provides a standardized benchmark for image classification algorithms in machine learning. The dataset contains grayscale images of fashion products such as shirts, shoes, coats, and bags, each labeled according to its clothing category. It was designed as a direct replacement for the original MNIST handwritten digits dataset, maintaining the same structure and image size so that researchers could easily switch datasets... -
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NTU RGB-D
Info and sample codes for "NTU RGB+D Action Recognition Dataset"
The “NTU RGB+D” repository provides access to a large-scale dataset for human action recognition (and its extension, NTU RGB+D 120). The dataset includes multiple modalities (RGB video, depth sequences, infrared video, 3D skeletal joint data) captured with multiple Kinect v2 cameras simultaneously. The repository also contains MATLAB / Python demo scripts for loading, visualizing, and processing skeleton data, mapping between modalities, and handling dataset structure. Multi-modal action... -
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Following Instructions with Feedback
Training Language Models to Follow Instructions with Human Feedback
...The repository is not a full implementation of the entire RLHF pipeline, but rather an archival hub supporting the published research—providing transparency around evaluation and human labeling standards. It includes directories such as automatic-eval-samples (samples of model outputs on benchmark tasks) and a model-card.md that describes the InstructGPT models’ intended behavior, limitations, and biases. -
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pyWhat
Identify emails, IP addresses, and more
...Given inputs such as hex strings, URLs, email addresses, IP addresses, credit card numbers, cryptocurrency wallets, or entire .pcap capture files, it scans for structured patterns and tells you what it finds. The tool is recursive: it can traverse files and directories to extract meaningful entities, which is useful when analyzing malware samples, network captures, or code repositories at scale. It offers powerful filters called “tags” and distributions that let you narrow results to specific categories like bug bounties, cryptocurrencies, or AWS-related artifacts. For automation and integration, pyWhat provides a CLI with options for rarity filtering, sorting, and JSON export, as well as an API that can be imported into other Python programs. -
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Learn and Play
XML-based framework for developing games
XML-based framework for developing games in (ActionScript 2.0, discontinued) HTML5 Phaser.io's engine It'd been thought to develope a project with a great amount of games on drag&drop, painting, typing, hunting, puzzles.There's no need to write the same code to similar games! Just write some XML lines (check samples) and one JavaScript instruction to run your game. NOTE: some browsers security policies do not allow to run samples locally. If this occurs, try to publish on a web site -
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XISMuS
X-Ray Imaging Software for Multiple Samples
...IMPORTANT FIXES in respect to base v2.0.0 version: v.2.5.0 introduces the Differential Attenuation and Cube Viewer utilities, and migrates user database to *.json files v2.4.3 fixes a with K element in the fit-approx method v2.4.3 fixes and issue where saving plots with fit-approx or a auto-wizard could freeze the software v2.4.2 introduces Image Viewer to Mosaic v2.4.1 fixes an issue in merging H5 or EDF datasets with Mosaic Full changelog at https://linssab.github.io/history X-Ray Fluorescence Imaging Software for Multiple Samples is an open source software to manipulate and study macro-X-Ray Fluorescence (MA-XRF) datasets. XISMuS also works as a sample management tool, where you can easily change between datasets (samples) and compare, cross-interact and normalize them. -
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protoFrameworkSamples
Samples for the protoFramework project
Samples for the protoFramework project. See https://sourceforge.net/projects/protoframework/ for the master project. This is a Dassault Aviation project -
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SVoice (Speech Voice Separation)
We provide a PyTorch implementation of the paper Voice Separation
SVoice is a PyTorch-based implementation of Facebook Research’s study on speaker voice separation as described in the paper “Voice Separation with an Unknown Number of Multiple Speakers.” This project presents a deep learning framework capable of separating mixed audio sequences where several people speak simultaneously, without prior knowledge of how many speakers are present. The model employs gated neural networks with recurrent processing blocks that disentangle voices over multiple...
