Search Results for "machine" - Page 76
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Showing 4715 open source projects for "machine"
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MeshCNN in PyTorch
Convolutional Neural Network for 3D meshes in PyTorch
MeshCNN is a deep learning framework designed specifically for processing 3D triangular mesh data using convolutional neural networks. Unlike traditional CNNs that operate on images or voxel grids, MeshCNN performs convolution operations directly on the edges of mesh structures. This design allows the model to capture geometric relationships between mesh elements while preserving the underlying topology of 3D shapes. The framework introduces specialized layers such as edge-based convolution,... -
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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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lightning library
Large-scale linear classification, regression and ranking in Python
lightning is a library for large-scale linear classification, regression and ranking in Python. -
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CodeSearchNet
Datasets, tools, and benchmarks for representation learning of code
...The dataset contains millions of pairs of source code functions and corresponding documentation comments extracted from open-source repositories. These pairs allow machine learning models to learn relationships between natural language descriptions and programming code. The dataset currently covers several widely used programming languages, including Python, JavaScript, Ruby, Go, Java, and PHP. In addition to the dataset itself, the repository includes baseline models, evaluation tools, and instructions for building code retrieval systems that can map user queries to relevant code snippets. -
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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AWS Step Functions Data Science SDK
For building machine learning (ML) workflows and pipelines on AWS
The AWS Step Functions Data Science SDK is an open-source library that allows data scientists to easily create workflows that process and publish machine learning models using Amazon SageMaker and AWS Step Functions. You can create machine learning workflows in Python that orchestrate AWS infrastructure at scale, without having to provision and integrate the AWS services separately. The best way to quickly review how the AWS Step Functions Data Science SDK works is to review the related example notebooks. ... -
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Covidex
Ultra fast and accurate subtyping tool of viral genomes.
Viral subtypes or clades represent clusters among isolates from the global population of a defined species. Subtypification is relevant for studies on virus epidemiology, evolution and pathogenesis. In this sense, Covidex was developed as an open source alignment-free machine learning subtyping tool. It is a shiny app that allows fast and accurate classification of viral genomes in pre-defined clusters. If more than 1000 sequences are loaded the tool will run in multithread mode. Capable of classifying 16000 genome sequences in less than a minute (AMD Ryzen 7 1700 8-core Processor 3 GHz) For a Web-based version of the app (only for small datasets: 100 seqs max) please go to http://covidex.unlu.edu.ar If you use Covidex please consider citing the following preprint: https://biorxiv.org/cgi/content/short/2020.08.21.261347v1 If you think my work is useful you can buy me a coffee! ... -
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Hugging Face Transformer
CPU/GPU inference server for Hugging Face transformer models
Optimize and deploy in production Hugging Face Transformer models in a single command line. At Lefebvre Dalloz we run in-production semantic search engines in the legal domain, in the non-marketing language it's a re-ranker, and we based ours on Transformer. In that setup, latency is key to providing a good user experience, and relevancy inference is done online for hundreds of snippets per user query. Most tutorials on Transformer deployment in production are built over Pytorch and FastAPI.... -
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Neuromancer Neurostim is a software developed by Tomas Erno Ukkonen (and Novel Insight). It shows pictures, keywords and sounds to create video to steer EEG to target states etc. This can be used to increase sleepiness etc. Machine learning neural nets and HMMs are used to process EEG measurements.
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Trellis
Trellis Programming System
JIT compiled abstract machine for the Trellis Programming System featuring multimethod dispatch and pseudo-assembly similar to ECMA335. -
PRTG Catches Network Issues Before They Cause DowntimeReactive troubleshooting usually means hearing about a problem from frustrated users, not your monitoring tool. PRTG sets threshold-based alerts across devices, servers and applications, notifying your team by email, SMS or push the moment a metric crosses a set limit. That means catching a failing disk or overloaded server before it becomes an outage and getting time back from firefighting. Start a free trial and set your first alerts today.
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e-Dokyumento
e-Dokyumento is web-based Document Management System (DMS)
e-Dokyumento is opensource web-based Document Management System (DMS) A Document Management which automates the basic office document workflow such as receiving, filing, routing, and approving through capturing (scanning), digitizing (OCR Reading), storing, tagging, and electronically routing and approving (e-signature) of electronic documents. # Demo : https://e-dokyumento.herokuapp.com/ https://edokyu.seillig.com/ (refer to Readme.md for the... -
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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. -
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Machine Learning in Asset Management
Machine Learning in Asset Management
Machine Learning in Asset Management is a research-oriented repository that explores how machine learning techniques can be applied to portfolio management and asset allocation. The project collects educational materials, code implementations, and experiments related to applying artificial intelligence methods in financial markets. It covers topics such as predictive modeling for asset prices, portfolio optimization strategies, and risk management using machine learning algorithms. ... -
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humanize
Python humanize functions
humanize is a Python utility library for converting machine-oriented numbers, dates, durations, and sizes into readable text. It can format large integers with separators or abbreviations such as millions and billions. Date and time helpers produce natural expressions such as relative times, human-readable dates, and approximate durations. Precise duration formatting can break intervals into days, hours, minutes, seconds, milliseconds, and smaller units. -
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Arxiv Sanity Lite
arxiv-sanity lite: tag arxiv papers of interest get recommendations
Arxiv Sanity Lite is a lightweight rewrite of Karpathy’s original arXiv discovery tool for tracking machine-learning research. It periodically polls the arXiv API for new papers and stores them locally for browsing. Users can tag papers they find relevant and receive recommendations tailored to each tag. Recommendations are generated with support vector machines trained on TF-IDF features extracted from paper abstracts. The web interface supports searching, ranking, sorting, and filtering the indexed collection. ... -
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PyTTI-Notebook
PyTTI-Notebook
Recent advances in machine learning have created opportunities for “AI” technologies to assist unlocking creativity in powerful ways. PyTTI is a toolkit that facilitates image generation, animation, and manipulation using processes that could be thought of as a human artist collaborating with AI assistants. The underlying technology is complex, but you don’t need to be a deep learning expert or even know coding of any kind to use these tools. -
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Machine Learning Financial Laboratory
MlFinLab helps portfolio managers and traders
...Its architecture emphasizes reproducibility, robust testing, and well-documented code so that researchers and practitioners can reliably experiment with financial machine learning models. -
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GiantMIDI-Piano
Classical piano MIDI dataset
...It provides a resource for music information retrieval (MIR), symbolic music modeling, composer classification, music generation, analysis of classical piano repertoire, and data-driven research in musicology or AI-based composition. Because the dataset is machine-generated via an automated transcription pipeline, it offers consistency, scale, and accessibility that would be difficult to achieve manually — enabling researchers to work with large corpora of piano music without copyright restrictions on symbolic data. -
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...It serves as framework for the development of - Dynamic and stable software - Modular software by the use of software components - Distributed applications - Highly complex machine controls with distributed logic It supports you in - Designing pervasive behavior in your applications - Language and platform independent interface definition using xIDL - Serializing objects - Distributing objects (remote method invocation) - Creating and using classes
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waybackpy
waybackpy : Python library that interfaces with the Internet Archive
Waybackpy is a Python library that interfaces with the Internet Archive's Wayback Machine API. Archive webpages and retrieve archived webpages easily. Also a command-line program. -
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Graph4NLP
Graph4nlp is the library for the easy use of Graph Neural Networks
Graph4NLP is an easy-to-use library for R&D at the intersection of Deep Learning on Graphs and Natural Language Processing (i.e., DLG4NLP). It provides both full implementations of state-of-the-art models for data scientists and also flexible interfaces to build customized models for researchers and developers with whole-pipeline support. Built upon highly-optimized runtime libraries including DGL , Graph4NLP has both high running efficiency and great extensibility. The architecture of... -
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MACE
Deep learning inference framework optimized for mobile platforms
Mobile AI Compute Engine (or MACE for short) is a deep learning inference framework optimized for mobile heterogeneous computing on Android, iOS, Linux and Windows devices. Runtime is optimized with NEON, OpenCL and Hexagon, and Winograd algorithm is introduced to speed up convolution operations. The initialization is also optimized to be faster. Chip-dependent power options like big.LITTLE scheduling, Adreno GPU hints are included as advanced APIs. UI responsiveness guarantee is sometimes... -
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DeepDanbooru
AI based multi-label girl image classification system
...The system uses convolutional neural networks trained on large datasets of tagged images to learn relationships between visual features and textual labels. Because the Danbooru dataset contains millions of images with extensive annotations, it provides a valuable training resource for machine learning models specializing in illustration analysis. Such datasets have been widely used for tasks including automatic image tagging, anime face detection, and generative modeling research. -
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Zenoss Community Edition
Zenoss - Intelligent IT Operations Management
Zenoss provides software-defined IT operations for the world’s largest organizations. We deliver the ultimate level of IT service health with simplicity by providing the most granular and intelligent IT service modeling possible, at any scale, and sharing these unique insights with other IT operations management (ITOM) tools to make them more efficient. Zenoss Community Edition is not a “demo” or trial version of Zenoss Enterprise or Zenoss Cloud! Before You install Zenoss Community... -
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AI Platform Training and Prediction
Cloud ML Engine repo
AI Platform Training and Prediction is a collection of machine learning example projects that demonstrate how to train, deploy, and serve models using Google Cloud AI Platform and related services. It includes a wide variety of implementations across frameworks such as TensorFlow, PyTorch, scikit-learn, and XGBoost, allowing developers to explore different approaches to building ML solutions. -
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Epoch Time
Setting virtual machines date and time using barcode reader offline
Written in c++ using qt4 libraries. For linux hosts and linux guests machines. Require installed package zint and qt4 libraries. - After save state, restore virtual machine. - Login as root. - Activate qr code displying function with countdown pressing 'qr' button. - With keyboard captured, click without releasing barcode reader button pointed over screen image during countdown. Can see PLAYME.mkv demo dowloadable as separate file in this project at sourceforge.
