Search Results for ".lab" - Page 7
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Showing 533 open source projects for ".lab"
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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VKO
GOST R 34.10-2012 VKO key agreement function (RFC 7836)
...It allows two parties to jointly agree on a shared secret using an insecure channel. This project is licensed under the ISC License. Copyright © 2020-2021 ALBANESE Research Lab Source code: https://github.com/pedroalbanese/vko Visit: http://albanese.atwebpages.com -
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LSHMAC
LSH-256 Hash-based Message Autentication Code Utility
This project is licensed under the ISC License. Copyright © 2020-2021 ALBANESE Research Lab Source code: https://github.com/pedroalbanese/lshsum Visit: http://albanese.atwebpages.com -
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XZ
Multi-core, cross-platform XZ compression tool written in Go
Parallel implementation of XZ for modern multi-core machines written in Go. This project is licensed under the ISC License. Copyright © 2020-2021 ALBANESE Research Lab Source code: https://github.com/pedroalbanese/xz-2 Visit: http://albanese.atwebpages.com -
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Brotli
Cross-platform Brotli Compression Tool written in Go
...It was translated from the reference implementation (https://github.com/google/brotli) This project is licensed under the MIT License. Copyright © 2020-2021 ALBANESE Research Lab Source code: https://github.com/pedroalbanese/brotli Visit: http://albanese.atwebpages.com -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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cccd
Simple astronomical CCD controller
This program supports TSNK-lab ICX285AL cameras, QHY5, QHY6, QHY9, QHY8L, QHY10, DSI2PRO, DSLR. It works with Mono images of 8, 12, 16 bits and RGB images of 24, 48 bits. Photo and video modes can be used. Histogram control of preview is available. There are two modes of capture: single frame mode and series. -
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Zstd
ZStandard Compression Utility written in Go
This project is licensed under the ISC License. Copyright © 2020-2021 ALBANESE Research Lab Source code: https://github.com/pedroalbanese/zstd Visit: http://albanese.atwebpages.com -
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GOST-Shred ☭
Cross-platform Shred implementation written in Golang
Commandline File Shredder - ALBANESE Lab (c) 2020-2021 GOST R 50739-95 Data Sanitization Method (2 passes). Prevents data recovery using standard recovery tools. Copyright © 2020-2021 ALBANESE Research Lab Source code: https://github.com/pedroalbanese/gost-shred Visit: http://albanese.atwebpages.com -
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X25519
NIST SP800-186 X25519 key agreement function written in Go
...Bernstein has since proposed that the name Curve25519 be used for the underlying curve, and the name X25519 for the DH function. This project is licensed under the ISC License. Copyright © 2020-2021 ALBANESE Research Lab Source code: https://github.com/pedroalbanese/x25519 Visit: http://albanese.atwebpages.com -
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Teachable Machine
Explore how machine learning works, live in the browser
Teachable Machine is the open-source implementation of an experimental machine learning tool created by Google Creative Lab that allows users to train simple machine learning models directly in a web browser. The project demonstrates how neural networks can be trained interactively using images captured from a webcam or other inputs without requiring programming knowledge. Users can provide example images for different categories, and the system trains a model that learns to classify those inputs in real time. ... -
Cut Data Warehouse Costs by 54%BigQuery delivers 54% lower TCO with exabyte scale and flexible pricing. Free migration tools handle the SQL translation automatically.
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Bzip2
Parallel implementation of Bzip2 for multi-core machines written in Go
Parallel implementation of Bzip2 for modern multi-core machines written in Go. This project is licensed under the ISC License. Copyright © 2020-2021 ALBANESE Research Lab Source code: https://github.com/pedroalbanese/bzip2 Visit: http://albanese.atwebpages.com -
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Gzip
Parallel implementation of Gzip for multi-core machines written in Go
Parallel implementation of Gzip for modern multi-core machines written in Go. This project is licensed under the ISC License. Copyright © 2020-2021 ALBANESE Research Lab Source code: https://github.com/pedroalbanese/gzip Visit: http://albanese.atwebpages.com -
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VPLE
Vulnerable Pentesting Lab Environment
VPLE (Linux) Vulnerable Pentesting Lab Environment VPLE is an Intentionally Vulnerable Linux Virtual Machine. This VM can be used to conduct security training, test security tools, and practice common penetration testing Labs. In VPLE bunch of labs are Available. NOTE:- "Only run in VMWare Pls Don’t run in VirtualBox" The default login and password is administrator: password. -
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GitPrep
Portable GitHub system into your own server
...Because it’s written in Perl and designed for simplicity, setup is often as easy as cloning, configuring a webroot, and pointing to repositories. Authentication and basic permissions can be configured, allowing private or team usage. Unlike full-featured Git lab or hosting suites, GitPrep focuses on just the browser view of repositories, staying lean and ideal for small teams or personal use. It’s sufficient for code review, history tracing, and lightweight dev workflows when elaborate ticketing or CI integrations aren’t required. -
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ACToolkit's temporary homepage
Max-objects-&-patches for Algorithmic Composition and statistical DSP
It was formerly jey-Toolkit. Now it's renamed and also being distributed by Cycling '74. Through the Files menu that appears above, the same package as released at the Package Manager of Max 7/8 and the beta-version update(s) are accessible. PLEASE NOTE that, on Max 6.1.10, some Jitter features and GEN~ objects that the patches included in the package use WON'T be working. The name of our package ACToolkit is a derivative of AC Toolbox, the legendary "Algorithmic music composition program... -
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dune-archiso
Archiso profile based on CyberOS with DUNE Numerics
This is a live USB containing a full operating system that can be booted, this means that you can use a USB stick to burn this image or virtualize it to Linux-KVM, QEMU, Virtualbox, VMWare, Hyper-V. We included the following Arch Linux official repositories: - [core] - [extra] - [community] - [multilib] as well as Third-party repositories: - [arch4edu] - [cyber] - [dune-archiso-repository-core] - [dune-archiso-repository-extra] - [dune-core] - [dune-staging] -... -
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AliceMind
ALIbaba's Collection of Encoder-decoders from MinD
This repository provides pre-trained encoder-decoder models and its related optimization techniques developed by Alibaba's MinD (Machine IntelligeNce of Damo) Lab. Pre-trained models for natural language understanding (NLU). We extend BERT to a new model, StructBERT, by incorporating language structures into pre-training. Specifically, we pre-train StructBERT with two auxiliary tasks to make the most of the sequential order of words and sentences, which leverage language structures at the word and sentence levels, respectively. ... -
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KISA Toolkit
Korea Internet & Security Agency's Cipher Suite written in Go
...Cryptographic Functions: • Symmetric Encryption/Decryption • Hash Digest • CMAC (Cipher-based message authentication code) • HMAC (Hash-based message authentication code) • PBKDF2 (Password-based key derivation function 2) Copyright (c) 2020-2021 Pedro Albanese - ALBANESE Lab Visit: http://albanese.atwebpages.com -
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uuid
Time-based UUID Generator/Parser written in Go
The uuid package generates and inspects UUIDs based on RFC 4122 and DCE 1.1: Authentication and Security Services. uuid:用 Go 编写的基于时间的 UUID 生成器/解析器-开源 DCE 1.1：身份验证和安全服务生成和检查 UUID。 Usage 用法: ./uuid [-d] Copyrigth (c) 2021 Pedro Albanese - ALBANESE Lab Visit: http://albanese.atwebpages.com -
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TNN
Uniform deep learning inference framework for mobile
TNN, a high-performance, lightweight neural network inference framework open sourced by Tencent Youtu Lab. It also has many outstanding advantages such as cross-platform, high performance, model compression, and code tailoring. The TNN framework further strengthens the support and performance optimization of mobile devices on the basis of the original Rapidnet and ncnn frameworks. At the same time, it refers to the high performance and good scalability characteristics of the industry's mainstream open source frameworks, and expands the support for X86 and NV GPUs. ... -
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aws_glue_databrew_jupyter
Manage your AWS Glue Databrew resources in-context
This is an extension for Jupyter Lab that allows you to manage your AWS Glue Databrew resources in-context of your existing Jupyter workflows. -
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DeepMind Lab
A customizable 3D platform for agent-based AI research
...If you use DeepMind Lab in your research and would like to cite the DeepMind Lab environment, we suggest you cite the DeepMind Lab paper. To enable compiler optimizations, pass the flag --compilation_mode=opt, or -c opt for short, to each bazel build, bazel test and bazel run command. The flag is omitted from the examples here for brevity, but it should be used for real training and evaluation where performance matters. -
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Self-Attentive Parser
High-accuracy NLP parser with models for 11 languages
LightAutoML is an automated machine learning (AutoML) framework developed by Sberbank AI Lab, designed to facilitate the development of machine learning models with minimal human intervention. -
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LearnCS8 Resume
Resume template website for the LearnCS8 Lab 3
LearnCS8-Resume is a template or demo project for a resume built as a web page (HTML/CSS/JS) for the LearnCS8 course’s Lab 3. It provides an example of a student project or assignment: a personal resume page implemented using front-end web technologies. HTML structure for resume content (education, experience, skills). Responsive or adaptive styling for various viewports. Sample placeholders/instructions for student substitution. -
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AmPEP and AxPEP
Sequence-based Antimicrobial Peptide Prediction by Random Forest
Antimicrobial peptides (AMPs) are promising candidates in the fight against multidrug-resistant pathogens due to its broad range of activities and low toxicity. However, identification of AMPs through wet-lab experiment is still expensive and time consuming. AmPEP is an accurate computational method for AMP prediction using the random forest algorithm. The prediction model is based on the distribution patterns of amino acid properties along the sequence. Our optimal model, AmPEP with 1:3 data ratio achieved a very high accuracy of 96%, MCC of 0.9, AUC-ROC of 0.99 and Kappa statistic of 0.9. ... -
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Fast and efficient 3D pharmacophore search developed by the Camacho Lab (http://smoothdock.ccbb.pitt.edu) at the University of Pittsburgh. Source code is available through the svn repository.
