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Showing 13 open source projects for "linux is"
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Automate contact and company data extractionGenerate leads at scale without building or maintaining scrapers. Use 10,000+ ready-made tools that handle authentication, pagination, and anti-bot protection. Pull data from business directories, social profiles, and public sources, then export to your CRM or database via API. Schedule recurring extractions, enrich existing datasets, and integrate with your workflows.
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Smart Business Texting that Generates PipelineTextUs is the leading text messaging service provider for businesses that want to engage in real-time conversations with customers, leads, employees and candidates. Text messaging is one of the most engaging ways to communicate with customers, candidates, employees and leads. 1:1, two-way messaging encourages response and engagement. Text messages help teams get 10x the response rate over phone and email. Business text messaging has become a more viable form of communication than traditional mediums. The TextUs user experience is intentionally designed to resemble the familiar SMS inbox, allowing users to easily manage contacts, conversations, and campaigns. Work right from your desktop with the TextUs web app or use the Chrome extension alongside your ATS or CRM. Leverage the mobile app for on-the-go sending and responding.
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Akka
Build concurrent, distributed, and resilient message-driven apps
Build powerful reactive, concurrent, and distributed applications more easily. Akka is a toolkit for building highly concurrent, distributed, and resilient message-driven applications for Java and Scala. Actors and Streams let you build systems that scale up, using the resources of a server more efficiently, and out, using multiple servers. Building on the principles of The Reactive Manifesto Akka allows you to write systems that self-heal and stay responsive in the face of failures. Up to... -
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Synapse Machine Learning
Simple and distributed Machine Learning
SynapseML (previously MMLSpark) is an open source library to simplify the creation of scalable machine learning pipelines. SynapseML builds on Apache Spark and SparkML to enable new kinds of machine learning, analytics, and model deployment workflows. SynapseML adds many deep learning and data science tools to the Spark ecosystem, including seamless integration of Spark Machine Learning pipelines with the Open Neural Network Exchange (ONNX), LightGBM, The Cognitive Services, Vowpal Wabbit,... -
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Scio
A Scala API for Apache Beam and Google Cloud Dataflow
Scio is a Scala API developed by Spotify that builds on Apache Beam to enable expressive batch and streaming data pipelines, optimized for running on Google Cloud Dataflow. Inspired by Spark and Scalding, it provides scalable, type‑safe, and production-grade data processing, with built-in support for BigQuery, Pub/Sub, Cassandra, Elasticsearch, Redis, TensorFlow IO, and more. -
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Cassandra Spark Connector
Apache Spark to Apache Cassandra connector
The Apache Cassandra Spark Connector allows Spark jobs (RDDs or DataFrames/Datasets) to read from and write to Cassandra tables. Compatible with Apache Cassandra (v2.1+), Spark 1.0–3.5, and Scala 2.11–2.13, it supports mapping Cassandra rows to Scala case classes, saving results back to Cassandra, and executing arbitrary CQL within Spark applications. -
Incredable is the first DLT-secured platform that allows you to save time, eliminate errors, and ensure your organization is compliant all in one place.Incredable streamlines and simplifies the complex process of medical credentialing for hospitals and medical facilities, helping you save valuable time, reduce costs, and minimize risks. With Incredable, you can effortlessly manage all your healthcare providers and their credentials within a single, unified platform. Our state-of-the-art technology ensures top-notch data security, giving you peace of mind.
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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)... -
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SnappyData
Memory optimized analytics database, based on Apache Spark
SnappyData (aka TIBCO ComputeDB) is a distributed, in-memory optimized analytics database. SnappyData delivers high throughput, low latency, and high concurrency for a unified analytics workload. By fusing an in-memory hybrid database inside Apache Spark, it provides analytic query processing, mutability/transactions, access to virtually all big data sources and stream processing all in one unified cluster. One common use case for SnappyData is to provide analytics at interactive speeds over... -
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rocket-bi
An open-source web-based self-service BI for analytical databases
Rocket.BI is a free, open-source, web-based business intelligence solution specifically designed for analytical databases. It enables data analysts and business users alike to easily integrate different data sources, perform advanced data analysis, ad hoc, and more. With an easy-to-use editor, you can create personalized reports, build interactive business dashboards and generate actionable business insights. Rocket.BI also allows collaboration as working together with other people in the... -
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SZT-bigdata
SZT‑bigdata is an open source project
SZT‑bigdata is an open-source project analyzing real Shenzhen metro (subway) card usage data using big‑data frameworks like Spark, Hadoop, Hive, Kafka, Flink, ClickHouse, HBase, and Elasticsearch. Aimed at exploring transit passenger flow patterns and system optimization using a variety of Scala-based technologies. -
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DISTOD
Distributed discovery of bidirectional order dependencies
The DISTOD data profiling algorithm is a distributed algorithm to discover bidirectional order dependencies (in set-based form) from relational data. DISTOD is based on the single-threaded FASTOD-BID algorithm [1], but DISTOD scales elastically to many machines outperforming FASTOD-BID by up to orders of magnitude. Bidirectional order dependencies (bODs) capture order relationships between lists of attributes in a relational table. They can express that, for example, sorting books by... -
Leverage AI to Automate Medical CodingAs a healthcare provider, you should be paid promptly for the services you provide to patients. Slow, inefficient, and error-prone manual coding keeps you from the financial peace you deserve. XpertDox’s autonomous coding solution accelerates the revenue cycle so you can focus on providing great healthcare.
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apache spark data pipeline osDQ
osDQ dedicated to create apache spark based data pipeline using JSON
This is an offshoot project of open source data quality (osDQ) project https://sourceforge.net/projects/dataquality/ This sub project will create apache spark based data pipeline where JSON based metadata (file) will be used to run data processing , data pipeline , data quality and data preparation and data modeling features for big data. This uses java API of apache spark. It can run in local mode also. Get json example at https://github.com/arrahtech/osdq-spark How to... -
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Cosmos DB Spark
Apache Spark Connector for Azure Cosmos DB
Azure Cosmos DB Spark is the official connector for Azure CosmosDB and Apache Spark. The connector allows you to easily read to and write from Azure Cosmos DB via Apache Spark DataFrames in Python and Scala. It also allows you to easily create a lambda architecture for batch-processing, stream-processing, and a serving layer while being globally replicated and minimizing the latency involved in working with big data. -
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Waterloo
Java-based scientific graphics
Java-based scientific graphics with support for Java, Groovy, MATLAB, Python, the R statistical environment, Scala and SciLab. -
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Java OpenCL Process Virtual Machine. Spring IoC based framework for complex data analysis with OpenCL computing.
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