Search Results for "process" - Page 3
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Showing 177 open source projects for "process"
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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AI Agents That Actually Do the WorkClickUp's Super Agents run 24/7 inside your workspace: triaging bugs, drafting content, updating statuses, and routing tasks without being told twice. Connect them to 500+ tools and let them execute, not just suggest. Build custom agents in minutes that understand your workflows and act on them autonomously.
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Datapipe
Real-time, incremental ETL library for ML with record-level depend
...Datapipe is designed to streamline the creation of data processing pipelines. It excels in scenarios where data is continuously changing, requiring pipelines to adapt and process only the modified data efficiently. This library tracks dependencies for each record in the pipeline, ensuring minimal and efficient data processing. -
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treeminder
a free mind mapping tool, to especially assist decision making
I've been trying to develop an idea of a project, but the wide range of possibilities with all their outcomes, cons and pros and whatnot got my mind overloaded. There was no way I could keep or process that much information with my bare mind. So, I've checked the mind mapping tools available in the market, both free and commercial ones, yet they were either clunky or overkilling for my needs. Thus, I've made my own thing, and decided to share it with everyone who might find it useful for their own things... -
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PlateEditor
PlateEditor, a free web application to work with multi-well plates
PlateEditor is a free web application to work with multi-well plates, from creation of layouts to data visualization and aggregation. It is primarily designed as a tool to help scientists working in the field of biology to simplify and fasten the process of data analysis. It is fully client-side: files are never transferred to the server, ensuring complete security and privacy of research data. It doesn't require any installation. - PlateEditor is available at this address: https://plateeditor.sourceforge.io - The source code is also available on GitHub, visit: https://github.com/vindelorme/PlateEditor More information about the source code and the API are available there (the wiki is still under construction, thanks for your patience!) ... -
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JLD.jl
Saving and loading julia variables while preserving native types
...For lossless storage of arbitrary Julia objects, the only other complete solution appears to be Julia's serializer, which can be accessed via the serialize and deserialize commands. However, because the serializer is also used for inter-process communication, long-term backward compatibility is currently uncertain. (The JLDArchives repository exists to test the compatibility of older JLD file formats.) If you choose to save data using the serializer, please use the file extension .jls to distinguish the files from .jld files. -
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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DocWire SDK
Award-winning modern data processing SDK in C++20
DocWire SDK, a standout C++20AI driven data processing tool, has received award from SourceForge and strong backing from Microsoft. It handles nearly 100 file types, empowering efficient text extraction, web data extraction, and document analysis. For businesses, the shift to DocWire SDK signifies a leap forward. It promises comprehensive document format support and the ability to extract valuable insights from email boxes, databases, and websites using cutting-edge AI. DocWire SDK aims to... -
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CiteSpace
A widely used tool for visual exploration of scientific literature.
Visit the new site: https://citespace.podia.com CiteSpace generates interactive visualizations of structural and temporal patterns and trends of a scientific field. It facilitates a systematic review of a knowledge domain through an in-depth visual analytic process. It can process citation data from popular sources such as the Web of Science, Scopus, Dimensions, and the Lens. CiteSpace also supports basic visual analytic functions for datasets without citation-related information, for example, PubMed, CNKI, ProQuest Dissertations and Theses. CiteSpace reveals how a field of research has evolved, what intellectual turning points are evident along a critical path, and what topics have attracted attention. ... -
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SageMaker Inference Toolkit
Serve machine learning models within a Docker container
Serve machine learning models within a Docker container using Amazon SageMaker. Amazon SageMaker is a fully managed service for data science and machine learning (ML) workflows. You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models. Once you have a trained model, you can include it in a Docker container that runs your inference code. A container provides an effectively isolated environment, ensuring a consistent runtime regardless of where the container is deployed. Containerizing your model and code enables fast and reliable deployment of your model. ... -
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Aestel
Applications for data management
...The AESTEL package contains two highly configurable applications for data management: A data loader and a reporting application, i.e. DataLoader and AEREA, respectively. The data loader application applies user-defined instructions to validate, process and load data. The reporting application provides a query builder and spreadsheet template designer. Both applications work with any relational data model. (Postgres and Oracle have been tested). The two applications have been initially developed for small molecule drug discovery research. However, they can be extended for use in other data domains. -
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Feathr
A scalable, unified data and AI engineering platform for enterprise
Feathr is a data and AI engineering platform that is widely used in production at LinkedIn for many years and was open sourced in 2022. It is currently a project under LF AI & Data Foundation. Define data and feature transformations based on raw data sources (batch and streaming) using Pythonic APIs. Register transformations by names and get transformed data(features) for various use cases including AI modeling, compliance, go-to-market and more. Share transformations and data(features)... -
Stop Cyber Threats with VM-Series Next-Gen Firewall on AzureGain integrated visibility across all traffic in a single pass. Deploy Palo Alto Networks VM-Series to determine application identity and content while automating security policy updates via rich APIs.
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Amazon Kinesis Flink Connectors
Contains various Apache Flink connectors to connect to AWS data
This library contains various Apache Flink connectors to connect to AWS data sources and sinks. This repository contains various Apache Flink connectors to connect to AWS Kinesis data sources and sinks. Flink maintain backwards compatibility for the Sink interface used by the Firehose Producer. This project is compatible with Flink 1.x, there is no guarantee it will support Flink 2.x should it release in the future. An Apache Flink application is a Java or Scala application that is created... -
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CSI-Math-Notation-PostfixInfix
Perl Lib Math Notation
... - Context validation can be implemented in item selection routines or data context validation, when it is possible to identify data to be selected or ignored in some data analysis process. * NOTE: - Before any implementation, we recommend details in WIKI (https://sourceforge.net/p/csi-math-notation-postfixinfix/wiki/) or the CPAN Perl Modules, see: https://metacpan.org/pod/Math::Notation::PostfixInfix * Support: The Support Service is FREE. Do you need support? Open a ticket and I will get back to you as soon as possible... -
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Weave Scope
Monitoring, visualization and management for Docker and Kubernetes
...Easily identify and correct issues to ensure the stability and performance of your containerized applications. View metrics, tags and metadata within the context of a process, container, service or host. Effortlessly navigate from processes inside your container to Docker hosts. Stop, start, pause and restart containers. View logs. Launch a command line. All without leaving Scope. Choose an overview of your container infrastructure, or focus on a specific microservice. Easily identify and correct issues to ensure the stability and performance of your containerized applications. -
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rayshade-mathematica
rayshade and POV for Mathematica Export + view
Beautifully Render* your Graphic3D and Shown or Manipulate right in the Front End (without Export to, ie 3DStudio Art Renderer, et al). For use with Mathematica 4.0 - 13.1. Makes file.ray or .pov that will look much like image in notebook except rendered. Works easily/automatically with many Graphics3D (and some Graphic) as well. However graphics in 13.1 is too big to comment on: many will work many not. Has many options to fix renders that aren't so auto. Now very portable... -
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Augmentor.jl
A fast image augmentation library in Julia for machine learning
A fast library for increasing the number of training images by applying various transformations. Augmentor is a real-time image augmentation library designed to render the process of artificial dataset enlargement more convenient, less error prone, and easier to reproduce. It offers the user the ability to build a stochastic image-processing pipeline (or simply augmentation pipeline) using image operations as building blocks. In other words, an augmentation pipeline is little more but a sequence of operations for which the parameters can (but need not) be random variables, as the following code snippet demonstrates. -
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AugmentedGaussianProcesses.jl
Gaussian Process package based on data augmentation, and sparsity
AugmentedGaussianProcesses.jl is a Julia package in development for Data Augmented Sparse Gaussian Processes. It contains a collection of models for different gaussian and non-gaussian likelihoods, which are transformed via data augmentation into conditionally conjugate likelihood allowing for extremely fast inference via block coordinate updates. There are also more options to use more traditional variational inference via quadrature or Monte Carlo integration. -
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Phiscal Web Client
VueJS Web Application
Application consumes endpoints served by the Phiscal RESTful API -
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Phiscal REST API
Phiscal Backend Interface
RESTful API to the Phiscal project, built with the Phalcon Micro Application class. -
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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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TheLib
Totally Helpful Extension classes for C++/C#
...All classes have multi-platform implementations, mainly Windows and Linux. Most classes focus on real-time computer graphics, scientific visualization, and corresponding data and process management. The Project was started at the Visualization Research Center of the University of Stuttgart (VISUS). -
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FLOGO
Simplify building efficient & modern serverless functions and apps
Project Flogo is an ultra-light, Go-based open source ecosystem for building event-driven apps. Event-driven, you say? Yup, the notion of triggers and actions are leveraged to process incoming events. An action, a common interface, exposes key capabilities such as application integration, stream processing, etc. All capabilities within the Flogo Ecosystem have a few things in common, they all process events (in a manner suitable for the specific purpose) and they all implement the action interface exposed by Flogo Core. ... -
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Amazon SageMaker Examples
Jupyter notebooks that demonstrate how to build models using SageMaker
Welcome to Amazon SageMaker. This projects highlights example Jupyter notebooks for a variety of machine learning use cases that you can run in SageMaker. If you’re new to SageMaker we recommend starting with more feature-rich SageMaker Studio. It uses the familiar JupyterLab interface and has seamless integration with a variety of deep learning and data science environments and scalable compute resources for training, inference, and other ML operations. Studio offers teams and companies... -
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Optimus
Agile Data Preparation Workflows made easy with Pandas
Easily write code to clean, transform, explore and visualize data using Python. Process using a simple API, making it easy to use for newcomers. More than 100 functions to handle strings, process dates, urls and emails. Easily plot data from any size. Out-of-box functions to explore and fix data quality. Use the same code to process your data in your laptop or in a remote cluster of GPUs. -
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OzGIS free open-source mapping system
Analysis and display of Census, business, government attribute data
OzGIS is an extensive mapping system for the analysis and display of geographically referenced data. Map data are downloaded from Census bureaux and map agencies or extracted from your own databases. The system can be used to to support management decisions associated with, for example, government planning, marketing, sales, site and personnel location, advertising and research. Systems for Windows, Mac and Ubuntu, source code, sample data files and manuals are included. DOWNLOAD to... -
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SageMaker Containers
Create SageMaker-compatible Docker containers
Amazon SageMaker is a fully managed service for data science and machine learning (ML) workflows. You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models. To train a model, you can include your training script and dependencies in a Docker container that runs your training code. A container provides an effectively isolated environment, ensuring a consistent runtime and reliable training process. The SageMaker Training Toolkit can be easily added to any Docker container, making it compatible with SageMaker for training models. ... -
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Strategems
Quantitative systematic trading strategy development and backtesting
Strategems is a Julia package aimed at simplifying and streamlining the process of developing, testing, and optimizing algorithmic/systematic trading strategies. This package is inspired in large part by the quantstrat1,2 package in R, adopting a similar general structure to the building blocks that make up a strategy. Given the highly iterative nature of event-driven trading strategy development, Julia's high-performance design (particularly in the context of loops) and straightforward syntax would seem to make it a natural fit as a language for systematic strategy research and development. ...
