Search Results for "applied"
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Showing 61 open source projects for "applied"
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Applied Infinity
MinusOneByTwelve Solutions LLP Repository
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labelme Image Polygonal Annotation
Image polygonal annotation with Python
... for instance segmentation. (instance segmentation). The first time you run labelme, it will create a config file in ~/.labelmerc. You can edit this file and the changes will be applied the next time that you launch labelme. If you would prefer to use a config file from another location, you can specify this file with the --config flag. -
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D2L.ai
Interactive deep learning book with multi-framework code
... to provide a starting point on the path to actually becoming an applied machine learning scientist. -
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Lightning Bolts
Toolbox of models, callbacks, and datasets for AI/ML researchers
Bolts package provides a variety of components to extend PyTorch Lightning, such as callbacks & datasets, for applied research and production. Torch ORT converts your model into an optimized ONNX graph, speeding up training & inference when using NVIDIA or AMD GPUs. We can introduce sparsity during fine-tuning with SparseML, which ultimately allows us to leverage the DeepSparse engine to see performance improvements at inference time. -
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Megatron
Ongoing research training transformer models at scale
Megatron is a large, powerful transformer developed by the Applied Deep Learning Research team at NVIDIA. This repository is for ongoing research on training large transformer language models at scale. We developed efficient, model-parallel (tensor, sequence, and pipeline), and multi-node pre-training of transformer based models such as GPT, BERT, and T5 using mixed precision. Megatron is also used in NeMo Megatron, a framework to help enterprises overcome the challenges of building... -
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MTEB
MTEB: Massive Text Embedding Benchmark
Text embeddings are commonly evaluated on a small set of datasets from a single task not covering their possible applications to other tasks. It is unclear whether state-of-the-art embeddings on semantic textual similarity (STS) can be equally well applied to other tasks like clustering or reranking. This makes progress in the field difficult to track, as various models are constantly being proposed without proper evaluation. To solve this problem, we introduce the Massive Text Embedding... -
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PyTorch Lightning
The lightweight PyTorch wrapper for high-performance AI research
.... When you need to scale up things like BERT and self-supervised learning, Lightning responds accordingly by automatically exporting to ONNX or TorchScript. PyTorch Lightning can easily be applied for any use case. With just a quick refactor you can run your code on any hardware, run distributed training, perform logging, metrics, visualization and so much more! -
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ConsoleMe
A central control plane for AWS permissions and access
ConsoleMe is a web service that makes AWS IAM permissions and credential management easier for end-users and cloud administrators. ConsoleMe provides numerous ways to log in to the AWS Console. An IAM Self-Service Wizard lets users request IAM permissions in plain English. Cross-account resource policies will be automatically generated and can be applied with a single click for certain resource types. Weep (ConsoleMe’s CLI) supports 5 different ways of serving AWS credentials locally. Cloud... -
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MathTranslate
translate scientific papers in latex, especially arxiv papers
This is a project to translate LaTeX documents, especially scientific papers, from any language to any language. LaTeX expressions like math expressions are perfectly kept unchanged. LaTeX documents can finally be compiled into PDF files. Especially it can be directly applied to translate arXiv papers since it provides the LaTeX source code of most of the papers. -
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MegaLinter
Mega-Linter analyzes 50 languages, 22 formats, 21 tooling formats etc.
Verify your code consistency with an open-source tool. MegaLinter is an Open-Source tool for CI/CD workflows that analyzes the consistency of your code, IAC, configuration, and scripts in your repository sources, to ensure all your projects sources are clean and formatted whatever IDE/toolbox is used by their developers, powered by OX Security. Supporting 54 languages, 24 formats, 22 tooling formats and ready to use out of the box, as a GitHub action or any CI system highly configurable and... -
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Lightly
A python library for self-supervised learning on images
A python library for self-supervised learning on images. We, at Lightly, are passionate engineers who want to make deep learning more efficient. That's why - together with our community - we want to popularize the use of self-supervised methods to understand and curate raw image data. Our solution can be applied before any data annotation step and the learned representations can be used to visualize and analyze datasets. This allows selecting the best core set of samples for model training... -
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High-Level Training Utilities Pytorch
High-level training, data augmentation, and utilities for Pytorch
Contains significant improvements, bug fixes, and additional support. Get it from the releases, or pull the master branch. This package provides a few things. A high-level module for Keras-like training with callbacks, constraints, and regularizers. Comprehensive data augmentation, transforms, sampling, and loading. Utility tensor and variable functions so you don't need numpy as often. Have any feature requests? Submit an issue! I'll make it happen. Specifically, any data augmentation, data... -
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DiLu Converter
A professional tool for importing and exporting Excel with database
DiLu Converter is a safe, fast and powerful Excel import and export tool. It supports multiple popular databases such as MySQL, Oracle, SQL Server, PostgreSQL, IBM DB2, Access, Hive, SQLite and Excel files in xls, xlsx, xlsm, xlsb, csv, txt and xml formats. It allows you to import and export in one step, in batch , in scheduled and in realtime For detail, Please see document: https://medium.com/@ryjfgjl.zhang/dilu-converter-documentation-05a50a8d0daa Contact: Email:... -
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PROPER Optical Propagation Library
Routines for wavefront propagation in IDL, Matlab, and Python
PROPER is a library of routines for the propagation of wavefronts through an optical system using Fourier-based methods. It was developed at the Jet Propulsion Laboratory for modeling stellar coronagraphs, but it can be applied to other optical systems were diffraction propagation is of concern. It is currently available for IDL (Interactive Data Language), Matlab and Python (3.x). It includes routines for generating complex apertures and obscurations and aberrations (Zernike & PSD-defined... -
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Tensorflow Transformers
State of the art faster Transformer with Tensorflow 2.0
Imagine auto-regressive generation to be 90x faster. tf-transformers (Tensorflow Transformers) is designed to harness the full power of Tensorflow 2, designed specifically for Transformer based architecture. These models can be applied on text, for tasks like text classification, information extraction, question answering, summarization, translation, text generation, in over 100 languages. Images, for tasks like image classification, object detection, and segmentation. Audio, for tasks like... -
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Japanese monospaced font Cica for programming. A monospaced Japanese font for programming, adjusted after synthesizing the following fonts. Hack + DejaVu Sans Mono for alphanumeric characters and symbols. Rounded Mgen+ for other characters. Nerd Fonts (= Powerline patch, others applied. Pomicons excluded*) Noto Emoji. Icons for Devs. Various adjustments forked from the Ricty generator. mShorten the middle bar as a unique adjustment (easy rnto mdistinguish & a little cute). Supports tmux split...
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Genode OS Framework
Tool kit for building highly secure special-purpose operating systems
... sub-sandboxes out of their own resources, thereby forming hierarchies where policies can be applied at each level. The framework provides mechanisms to let programs communicate with each other and trade their resources, but only in strictly-defined manners. Thanks to this rigid regime, the attack surface of security-critical functions can be reduced by orders of magnitude compared to contemporary operating systems. -
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AugLy
A data augmentations library for audio, image, text, and video
AugLy is a data augmentations library that currently supports four modalities (audio, image, text & video) and over 100 augmentations. Each modality’s augmentations are contained within its own sub-library. These sub-libraries include both function-based and class-based transforms, composition operators, and have the option to provide metadata about the transform applied, including its intensity. AugLy is a great library to utilize for augmenting your data in model training, or to evaluate... -
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OmicSelector
Feature selection and deep learning modeling for omic biomarker study
OmicSelector is an environment, Docker-based web application, and R package for biomarker signature selection (feature selection) from high-throughput experiments and others. It was initially developed for miRNA-seq (small RNA, smRNA-seq; hence the name was miRNAselector), RNA-seq and qPCR, but can be applied for every problem where numeric features should be selected to counteract overfitting of the models. Using our tool, you can choose features, like miRNAs, with the most significant... -
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Wicogen-windows-icon-generator
Windows folder icon generator
Wicogen Easily Customize your folders and make Windows suite to your taste! Just choose an image and it will be automatically applied to a folder of your choice! Quickly search the net for images you like by a folder name and a search term! Supported sources for online search: Google images Bing images IMDB (covers for movies and TV shows) MyAnimeList.net (covers for anime and movies) For Movie/TV, I recommend the disk style available in the "Style:" drop-down. If you find all... -
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Sezioni
Python tool for section property evaluation and stress calculation
This software is a basic tool for section property evaluation and stress calculation, written in python. The section can be imported or input by points and then can be modified moved, rotated etc.. Area and section inertia can be exported. Loads can be applied (multiple load cases can be imported) and the related stresses are calculated by mean of De Saint Venant formulas. Results are plot with selectable color maps. Point results are listed and may be exported. Section can be also input... -
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pipeless
A computer vision framework to create and deploy apps in minutes
Pipeless is an open-source computer vision framework to create and deploy applications without the complexity of building and maintaining multimedia pipelines. It ships everything you need to create and deploy efficient computer vision applications that work in real-time in just minutes. Pipeless is inspired by modern serverless technologies. It provides the development experience of serverless frameworks applied to computer vision. You provide some functions that are executed for new video... -
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VSGAN
VapourSynth Single Image Super-Resolution Generative Adversarial
Single Image Super-Resolution Generative Adversarial Network (GAN) which uses the VapourSynth processing framework to handle input and output image data. Transform, Filter, or Enhance your input video, or the VSGAN result with VapourSynth, a Script-based NLE. You can chain models or re-run the model twice-over (or more). Have low VRAM? Don’t worry! The Network will be applied in quadrants of the image to reduce up-front VRAM usage. You can use any RGB video input, including float32 (e.g., RGBS... -
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mlcourse.ai
Open Machine Learning Course
mlcourse.ai is an open Machine Learning course by OpenDataScience (ods.ai), led by Yury Kashnitsky (yorko). Having both a Ph.D. degree in applied math and a Kaggle Competitions Master tier, Yury aimed at designing an ML course with a perfect balance between theory and practice. Thus, the course meets you with math formulae in lectures, and a lot of practice in a form of assignments and Kaggle Inclass competitions. Currently, the course is in a self-paced mode. Here we guide you through the self... -
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Robust Video Matting (RVM)
Robust Video Matting in PyTorch, TensorFlow, TensorFlow.js, ONNX
... and matting quality. Furthermore, we propose a novel training strategy that enforces our network on both matting and segmentation objectives. This significantly improves our model's robustness. Our method does not require any auxiliary inputs such as a trimap or a pre-captured background image, so it can be widely applied to existing human matting applications. RVM is specifically designed for robust human video matting.