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Showing 3594 open source projects for "ekho-data"
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Demo Series - Small Business Backup By VeeamWatch this on-demand demo series and learn how to protect your Microsoft 365 data with clear, simple, actionable steps that are easy to implement for businesses of all sizes.
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Build Securely on AWS with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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PyX is a Python package for the creation of EPS, PS, PDF and SVG files. It combines an abstraction of the PostScript drawing model with a TeX/LaTeX interface. Complex tasks like 2d and 3d plots in publication-ready quality are built out of these primitives.
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tinfoleak
OSINT tool for extracting and analyzing Twitter intelligence data
...It also processes content such as hashtags, mentions, media files, and metadata to identify trends and relevant connections. Additional analysis features help uncover geolocation information, visited places, and user movement patterns when location data is available. -
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Zhao
A compilation of "The Princely Party Relationship Network"
zhao is a repository that consolidates research, data, and insights related to Zhao, which is likely an individual’s research collection, notes, or curated resources on deep learning, AI, or computational topics (name and content context suggest specialized study). The project may include code examples, experiment results, references to academic papers, mathematical notes, and supporting scripts to explore specific ML methods, benchmarks, or theoretical findings. -
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pyspider
A powerful Spider(Web Crawler) system in Python
...Or using MySQL or MongoDB and RabbitMQ to deploy a distributed crawl cluster. To deploy pyspider in product environment, running component in each process and store data in database service is more reliable and flexible. To deploy pyspider components in each single processes, you need at least one database service. pyspider now supports MySQL, MongoDB and PostgreSQL. You can choose one of them. -
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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Learn Python the Hard Way
Concise study notes derived from “Learn Python the Hard Way”
This repository contains concise study notes derived from “Learn Python the Hard Way,” organized to reinforce core Python concepts through small, targeted examples. It emphasizes hands-on practice—short scripts, exercises, and explanations that help cement syntax, data structures, functions, and modules. The notes call out common gotchas, idioms, and style preferences so learners form good habits early. Because the content is intentionally compact, it’s easy to revisit a topic quickly when preparing for interviews or refreshing fundamentals. The material favors clarity over abstraction, keeping examples runnable and easy to modify in any editor. ... -
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pyNETVARS
Python module for network variables for CoDeSys PLCs
CoDeSys v2.3 supports so called network variables. Blocks of (global) variables, that propagates over networks like TCP, UDP or UDP Multicast aso. This python module supports parsing, receiving and sending those blocks (with UDP Multicast only). With this you can add for example a Raspberry Pi Sensor to your automation network without special Network clients on your PLC. -
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MAD-X Python Builder
Build windows executable from Python file. Easily compiler your Python
Build windows executable from your Python file, with areas that requires your program info, description, Icon etc. It is possible to load existing data sets, given they are under corresponding Pickle formats, while saving also generates an Pickle file. Info fields can meet most demands, Windowed or consoled program type. One-file or Folder package, Encryption module, Hidden-Imports, UPX Compatible, Icon, program end-name, Debug mode and more. -
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DIGITS
Deep Learning GPU training system
The NVIDIA Deep Learning GPU Training System (DIGITS) puts the power of deep learning into the hands of engineers and data scientists. DIGITS can be used to rapidly train the highly accurate deep neural network (DNNs) for image classification, segmentation and object detection tasks. DIGITS simplifies common deep learning tasks such as managing data, designing and training neural networks on multi-GPU systems, monitoring performance in real-time with advanced visualizations, and selecting the best performing model from the results browser for deployment. ... -
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Vaex
Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python
Data science solutions, insights, dashboards, machine learning, deployment. We start at 100GB. Vaex is a high-performance Python library for lazy Out-of-Core data frames (similar to Pandas), to visualize and explore big tabular datasets. It calculates statistics such as mean, sum, count, standard deviation etc, on an N-dimensional grid for more than a billion (10^9) samples/rows per second. -
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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MultiBootUSB
Create multiboot live Linux on a USB disk
MultiBootUSB is a cross platform* software/utility to create multi boot live Linux on a removable USB disk. It is similar to UNetbootin but many distros can be installed, provided you have enough space on the disk. MultiBootUSB also provides an option to uninstall distro(s) at any time, if you wish. -
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jsondata
Modular JSON by trees and branches, pointers and patches
The 'jsondata' package provides for the modular in-memory processing of JSON data by trees, branches, pointers, and patches. The main interface classes are: - JSONData - Core for RFC7159 based data structures. Provides modular data components. - JSONDataSerializer - Core for RFC7159 based data persistence. Provides modular data serialization. - JSONPointer - RFC6901 for addressing by pointer paths. Provides pointer arithmetics -
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DC-TTS
TensorFlow Implementation of DC-TTS: yet another text-to-speech model
...The model is split into two networks: Text2Mel, which maps text to mel-spectrograms, and SSRN (spectrogram super-resolution network), which converts low-resolution mel-spectrograms into high-resolution magnitude spectrograms suitable for waveform synthesis. Training scripts, data loaders, and hyperparameter configurations are provided to reproduce results on several datasets, including LJ Speech for English, a Korean single-speaker dataset, and audiobook data from Nick Offerman and Kate Winslet. -
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xmgrace python interface
xmgrace and qtgrace plotting interface in python
This is a python module providing a nearly complete interface to the graphing program xmgrace and the new qtgrace (great project... grace works under windows, too, now!). It allows creation of grace plots from within python, which can be customized using python, or through grace after creation. -
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AutotestnetServer
Server part of autotestnet net edition (since 2.0)
This project is used for server side of autotestnet (start from version 2.0) net edition. From v2.0, autotestnet use http to contact server(mysql) for all data storage, and a public service site was launched in pythonanywhere to support this. Before that, it contact mysql server directly by mysqltcl which need user to maintain mysql server by themselves, and, install mysqltcl is also a pain sometimes. -
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pyhanlp
Chinese participle
...It is commonly used for Chinese-language NLP tasks where you want production-grade tokenization and linguistic analysis, but still want the convenience of Python scripting. The project focuses on making HanLP’s capabilities accessible through a Python-friendly API surface, so you can integrate NLP steps into data pipelines, notebooks, and downstream ML or information-extraction code. In practice, it serves as a bridge layer: Python calls are translated into the corresponding HanLP operations, so you can keep your application logic in Python while relying on HanLP’s implementations. It is especially useful when you need a pragmatic “get results quickly” NLP layer for segmentation, tagging, entity extraction, parsing, or keyword-style tasks rather than experimenting with model training from scratch. -
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...Algorithm implementation for population pharmacokinetic analysis: The current project describes the marriage between PBPK modeling and population-based statistical analysis. The latter is necessary for parameter estimation when individual-level data is available. A critical aspect of this coupling is the implementation of an algorithm that would allow the performance of population-based statistical analysis. Although novelty is encouraged in regards to the algorithm, proposals could entertain approaches such as: a. Implementing the non-linear mixed effects theory, b. Maximum log-likelihood algorithms (stiff, non-stiff Ordinary Differential Equation solving methods with linearization)
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Siamese and triplet learning
Siamese and triplet networks with online triplet mining in PyTorch
...The repository demonstrates how to train these models using contrastive loss and triplet loss functions, which encourage embeddings of similar samples to be close while pushing dissimilar samples farther apart. It includes data loaders, training scripts, neural network architectures, and evaluation metrics that allow researchers to experiment with different embedding learning strategies. The project also implements online pair and triplet mining techniques to efficiently generate training examples during model training. -
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haipproxy
Distributed proxy IP pool for web crawlers using Scrapy and Redis
...It automatically crawls proxy resources from the internet and aggregates them into a centralized pool that can be accessed by distributed spiders and scraping systems. It is built using Python and relies on Scrapy for high-performance crawling while Redis is used for data storage, communication, and task coordination between components. It includes crawlers that discover proxy servers, validators that test proxy availability and performance, and schedulers that manage crawling and validation tasks. HAipproxy aims to maintain a high availability proxy pool with low latency so that scraping frameworks can rotate proxies efficiently and avoid blocking during large-scale data collection. ... -
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TEACUP
TCP Experiment Automation Controlled Using Python
...When multiple values are provided (e.g. for TCP congestion control algorithm), an experiment is made up of multiple tests. For each experiment and test, TEACUP collects a range of data, such as tcpdump files of traffic seen or TCP stack information (e.g. using Web10G). TEACUP also collects a variety of metadata from the end hosts and bottleneck router, such as the actual OS/kernel version(s) used. TEACUP also provides some simple tools for analysing the results of experiments, such as plotting a flow's experienced RTT over time. -
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survol
RDF-based framework monitoring business systems activity
A Python agent and a web interface aiming to help the analysis and investigation of a legacy application. A set of machines, processes, databases, programs etc ... all communicating with each other, manipulating your data, and whose software architecture has become, with time, complicated, difficult to understand, and undocumented. Data are aggregated with an RDF inference engine, creating a global vision of the business information processing. -
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Serenata de Amor
Artificial Intelligence for social control of public administration
...Machine learning techniques and data analysis pipelines are used to identify anomalies that may indicate misuse of public funds. The system also includes automated tools that assist in processing large datasets and generating reports about potentially problematic transactions. By making both the data and the analysis tools open source, the project encourages civic participation and collaborative oversight of government activities. -
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FAKE2DB
Create custom test databases that are populated with fake data
...Username for the database user. password argument is OPTIONAL. Password for database user. Only supported for mysql & PostgreSQL. locale argument is OPTIONAL. The localization of data to be generated ('en_US' as default). seed argument is OPTIONAL. Integer for seeding random generator to produce the same data set between runs. Note: uuid4 values still generated randomly. -
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My Beaglebone Black Project
show and configure
The Beaglebone Black project presented here is a software written by Python and Qt and is intended to show the simple control of inputs and outputs (GPIO), the graphic course of input signals GPIO, the configuration and sending and receiving of data via the UART interfaces, the display of the PIN configuration of the Beaglebone Black and the graphic display of the signal course at the analog inputs. The software runs on the BBB under Debian 8.9 and on Linux computers (as a demo). It is intended to demonstrate the interaction of software with hardware and to encourage the development of peripheral hardware that works with the software described here. ... -
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RaspberryPi_LedSign
Python code drive PT6961 Led Sign AH41-01158A
This Simple project demonstrates how to send command and data to a PT6961 LED driver with a RaspberryPi by using Python. The Led Sign board (AH41-01158A) has been taken from an old Home Theater. A RaspberryPi model B has been used to communicate with. This code will ask the user to enter a sentence and will display this sentence 4 times. -
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pivottablejs
Drag’n’drop Pivot Tables and Charts for Jupyter/IPython Notebook
PivotTable.js is a Javascript Pivot Table and Pivot Chart library with drag-drop interactivity, and it can now be used with Jupyter/IPython Notebook via the pivottablejs module. I first built PivotTable.js with a plan to build an in-browser data analysis tool, and got as far as one where you could load up a CSV file in the browser for display. Since then, however, the Jupyter project has gathered steam and now provides a browser-based interface to some of the most powerful data processing libraries in the world, so it makes sense to interface with it.