Search Results for "data" - Page 65
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Showing 3125 open source projects for "data"
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Deploy Apps in Seconds with Cloud RunCloud Run is the fastest way to deploy containerized apps. Push your code in Go, Python, Node.js, Java, or any language and Cloud Run builds and deploys it automatically. Get fast autoscaling, pay only when your code runs, and skip the infrastructure headaches. Two million requests free per month. And new customers get $300 in free credit.
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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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Leo is an outlining-oriented project manager and browser. With Leo you can organize programs, web sites, URL's, pictures or any other kind of data. Leo is fully scriptable in Python. Leo is 100% pure Python. It requires the Qt gui toolkit.
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anaGo
Bidirectional LSTM-CRF and ELMo for Named-Entity Recognition
anaGo is a Python library for sequence labeling(NER, PoS Tagging,...), implemented in Keras. anaGo can solve sequence labeling tasks such as named entity recognition (NER), part-of-speech tagging (POS tagging), semantic role labeling (SRL) and so on. Unlike traditional sequence labeling solver, anaGo doesn't need to define any language-dependent features. Thus, we can easily use anaGo for any language. In anaGo, the simplest type of model is the Sequence model. Sequence model includes... -
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iTelliHashCSV
Cryptographic Hashing Application for CSV Files
iTelliHashCSV is a cryptographic “one-way” hashing application designed to securely protect sensitive or private information from disclosure. Proper use of this program allows organizations, businesses, and individuals (i.e., the data owners) to share complete/intact datasets containing sensitive data with others without actually disclosing the sensitive or private information. Additionally, if such datasets are subsequently modified or enhanced through value-added services or products provided by other organizations or individuals and then returned, the data owner retains the ability to “re-map” the hashed sensitive data values back to their original values. -
99.99% Uptime for MySQL and PostgreSQL on Google CloudCloud SQL Enterprise Plus gives you a 99.99% availability SLA with near-zero downtime maintenance—typically under 10 seconds. Get 2x better read/write performance, intelligent data caching, and 35 days of point-in-time recovery. Supports MySQL, PostgreSQL, and SQL Server with built-in vector search for gen AI apps. New customers get $300 in free credit.
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AerinSistemas-Noname
Elasticsearch to Pandas dataframe or CSV
API and command line utility, written in Python, for querying Elasticsearch exporting result as documents into a CSV file. The search can be done using logical operators or ranges, in combination or alone. The output can be limited to the desired attributes. Also ToT can insert the querying to a Pandas Dataframe or/and save its in a HDF5 container (under development). -
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iTelliHashExcel
Cryptographic Hashing Application for Excel Files
iTelliHashExcel is a cryptographic “one-way” hashing application designed to securely protect sensitive or private information from disclosure. Proper use of this program allows organizations, businesses, and individuals (i.e., the data owners) to share complete/intact datasets containing sensitive data with others without actually disclosing the sensitive or private information. Additionally, if such datasets are subsequently modified or enhanced through value-added services or products provided by other organizations or individuals and then returned, the data owner retains the ability to “re-map” the hashed sensitive data values back to their original values. -
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Now maintained at github.com/spacepy/spacepy Space Science library for Python - contains superposed epoch classes, drift shell tracing, access to magnetic field models, streamline tracing, bootstrap confidence limits, time and coordinate conversions, etc.
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Charting tools, backtesting tools, and data visualization tools for the most popular cryptocurrencies.
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GDL - GNU Data Language, a free IDL (Interactive Data Language, see http://ittvis.com/idl/) compatible incremental compiler.
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AI-powered service management for IT and enterprise teamsGive your IT, operations, and business teams the ability to deliver exceptional services—without the complexity. Maximize operational efficiency with refreshingly simple, AI-powered Freshservice.
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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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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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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. -
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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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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. -
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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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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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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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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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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.
