Search Results for "ekho-data" - Page 70
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Showing 3594 open source projects for "ekho-data"
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TransPose
PyTorch Implementation for "TransPose, Keypoint localization
TransPose is a human pose estimation model based on a CNN feature extractor, a Transformer Encoder, and a prediction head. Given an image, the attention layers built in Transformer can efficiently capture long-range spatial relationships between keypoints and explain what dependencies the predicted keypoints locations highly rely on. -
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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. The template includes configuration files, scripts, and project structures that help teams build reproducible experiments and production-ready pipelines. ... -
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HomeTabs
HomeTabs project helps you to organize bookmarks for web browsers
HomeTabs project helps you to organize bookmarks for web browsers (like a standart browser's home page, but cooler and more comfortable). Design of HomeTabs was inspiried by Mozilla Firefox startpage, i think this is the best way to organise bookmarks, but history of browsing saved on homepage - is bad idea. GitHub: https://github.com/grildroid/HomeTabs Discord: https://discord.gg/6ZGDgFjDVm -
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PyCls
Codebase for Image Classification Research, written in PyTorch
pycls is a focused PyTorch codebase for image classification research that emphasizes reproducibility and strong, transparent baselines. It popularized families like RegNet and supports classic architectures (ResNet, ResNeXt) with clean implementations and consistent training recipes. The repository includes highly tuned schedules, augmentations, and regularization settings that make it straightforward to match reported accuracy without guesswork. Distributed training and mixed precision are... -
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Ansible Role: prometheus
Deploy Prometheus monitoring system
Ansible-Prometheus is an Ansible role for automating the deployment and configuration of Prometheus monitoring systems. -
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DrQA
Reading Wikipedia to Answer Open-Domain Questions
...The retriever relies on classic IR features (like TF-IDF and n-gram statistics) to remain lightweight and scalable to millions of documents. The reader is a neural model trained on supervised QA data to estimate start and end positions within a paragraph, and it can be adapted to new domains through fine-tuning or distant supervision. The repository includes scripts to build the Wikipedia index, train the reader, and evaluate end-to-end performance. DrQA popularized a practical recipe for combining IR and neural reading, and it remains a strong baseline for open-domain QA research and production prototypes. -
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Earth Enterprise
Google Earth Enterprise - Open Source
Earth Enterprise is the open source version of Google Earth Enterprise (GEE), a powerful geospatial application suite that enables organizations to build and host custom 3D globes and 2D maps using their own imagery and data. Unlike Google Maps or Google Earth, Earth Enterprise does not include Google’s proprietary imagery but instead provides the tools needed to manage and visualize private geospatial datasets. The system is composed of three main components: Fusion, which processes and integrates imagery, vector, and terrain data into unified map layers; Server, which hosts the resulting globes or maps via Apache or Tornado-based web servers; and Client, which includes the Google Earth Enterprise Client (EC) for 3D visualization and the Google Maps JavaScript API V3 for 2D viewing. ... -
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Pytorch Points 3D
Pytorch framework for doing deep learning on point clouds
...Core implementation of common components for point cloud deep learning - greatly simplifying the creation of new models. 4 Base Convolution base classes to simplify the implementation of new convolutions. Each base class supports a different data format. -
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Steam Career
Generate webpages of your Steam player data
Python application which uses the Steam Web API to retrieve player data and present an overview in HTML form. This project is not endorsed in any way by Valve Corporation. -
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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. ... -
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Denoiser
Real Time Speech Enhancement in the Waveform Domain (Interspeech 2020)
...It uses a causal encoder-decoder architecture with skip connections, optimized with losses defined both in the time domain and frequency domain to better suppress noise while preserving speech. Unlike models that operate on spectrograms alone, this design enables lower latency and coherent waveform output. The implementation includes data augmentation techniques applied to the raw waveforms (e.g. noise mixing, reverberation) to improve model robustness and generalization to diverse noise types. The project supports both offline denoising (batch inference) and live audio processing (e.g. via loopback audio interfaces), making it practical for real-time use in calls or recording. ... -
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Big List of Naughty Strings
List of strings which have a high probability of causing issues
The Big List of Naughty Strings is a community-maintained catalog of “gotcha” inputs that commonly break software, from unusual Unicode to SQL and script injection payloads. It exists so developers and QA engineers can easily test edge cases that normal test data would miss, such as zero-width characters, right-to-left marks, emojis, foreign alphabets, and long or malformed strings. By throwing these strings at forms, APIs, databases, and UIs, teams can discover encoding bugs, sanitizer gaps, rendering issues, and security oversights early. The list is language-agnostic and repository-friendly, meaning you can consume it from CI pipelines or local scripts with minimal setup. ... -
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speedtest-cli
Command line interface for testing internet bandwidth using speedtest
...Test the internet connection of your Linux desktop, a remote server or even lower-powered devices such as the Raspberry Pi with the Speedtest Server Network. Set up automated scripts to collect connection performance data, including trends over time. -
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Text Gen
Almost state of art text generation library
...Text gen is a python library that allow you build a custom text generation model with ease. Something sweet built with Tensorflow and Pytorch(coming soon). Load your data, your data must be in a text format. Download the example data from the example folder. Tune your model to know the best optimizer, activation method to use. -
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MLOps Course
Learn how to design, develop, deploy and iterate on ML apps
The MLOps Course by Goku Mohandas is an open-source curriculum that teaches how to combine machine learning with solid software engineering to build production-grade ML applications. It is structured around the full lifecycle: data pipelines, modeling, experiment tracking, deployment, testing, monitoring, and iteration. The repository itself contains configuration, code examples, and links to accompanying lessons hosted on the Made With ML site, which provide detailed narrative explanations and diagrams. Instead of focusing only on model training, the course emphasizes best practices like modular code design, CI/CD, containerization, reproducibility, and responsible ML (including monitoring and feedback loops). ... -
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XLM (Cross-lingual Language Model)
PyTorch original implementation of Cross-lingual Language Model
XLM (Cross-lingual Language Model) is a family of multilingual pretraining methods that align representations across languages to enable strong zero-shot transfer. It popularized objectives like Masked Language Modeling (MLM) across many languages and Translation Language Modeling (TLM) that jointly trains on parallel sentence pairs to tighten cross-lingual alignment. Using a shared subword vocabulary, XLM learns language-agnostic features that work well for classification and sequence... -
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MetaHash
#MetaHash is a next-generation network based on the Blockchain 4.0
...The #MetaHash project implements a solution that simultaneously possesses all the qualities of Blockchain new generation, namely: - Decentralization, which ensures absolute trust of users to the network; - Full synchronization, thanks to which each user has instant access to the most relevant data; - А transaction speed of up to 3 seconds, which provides unconditional ease of system using and a guarantee of the full operation of decentralized applications; - High bandwidth, which allows the network to keep transaction prices low due to the fact that a similar amount of resources can confirm more transactions per unit time; - Low commissions, due to which a huge number of potential customers will be interested in using the network for transfer and storage of payment means and technical data... -
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PS-Drone
Programming a Parrot AR.Drone 2.0 with Python - The Easy Way
The PS-Drone-API is a full featured SDK, written in and for Python, for Parrot's AR.Drone 2.0. It was designed to be easy to learn, but it offers the full set of the possibilities of the AR.Drone 2.0, including Sensor-Data (aka NavData), Configuration and full Video-support. The video function is not restricted to mere viewing, it is also possible to analyze video images data using OpenCV2. Obviously, the PS-Drone is perfect for teaching purposes; however, even the requirements for professional purposes can be satisfied. PS-Drone comes with a tutorial, explaining its most important commands and the drone's most important sensor values. ... -
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Pension-Calculator
A simple retirement benefit calculator app written in python with GUI.
A simple retirement benefit calculator app written in python with GUI specifically for West Bengal State Govt. employees (India). This app is not associated with Govt. of West Bengal. This app is for informational purpose only. This project is open source under GNU public license v3.0 -
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BMC
Notes on Scientific Computing for Biomechanics
This repository is a collection of lecture notes and code on scientific computing and data analysis for Biomechanics and Motor Control. -
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earthengine-py-notebooks
A collection of 360+ Jupyter Python notebook examples
...Users can quickly adapt the examples for their own remote sensing, environmental monitoring, or spatial data science projects, and can run the code in environments like Google Colab. -
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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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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 during training. Considered as the go-to scheduler for semantic segmentation. ... -
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Keepsake
Version control for machine learning
Keepsake is a Python library that uploads files and metadata (like hyperparameters) to Amazon S3 or Google Cloud Storage. You can get the data back out using the command-line interface or a notebook. -
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Sar2html is web based frontend for performance monitoring. It converts sar binary data to graphical format and keep historical data in it's database. Project homepage is here: https://github.com/cemtan/sar2html.git Supported Operating Systems: HPUX 11.11, 11.23, 11,31 Solaris 5.9, 5.10, 5.11 Redhat 3, 4, 5, 6, 7 Suse 8, 9, 10, 11, 12 Ubuntu 18, 20 If you have customers facing performance problems on operating systems listed above you may send sar2ascii to collect performance data. ...