Code fusion in rubiscape gives an ingenious option to the users to build their models in programming languages such as JAVA, R, or Python and integrate them into rubiscape.
Code fusion makes the rubiscape platform more customizable and user-friendly.
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Reader in rubiscape is referred to as a dataset.
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Dataset
rubicast is an integrated tool to streamline and automate the forecasting process. With rubicast, one can efficiently explore and analyse large volumes of time-series data without manually coding models.
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rubiflow is an integrated process designer to help users build and manage data flows with a visual, end-to-end event-based orchestrator. The data access engines of rubiflow provide a powerful, easy-to-use user interface that facilitates seamless collaboration and reuse of processes and common metadata.
In rubiflow, we handle data and perform data orchestration (check the accuracy of existing models) for which multiple models are available.
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rubiML is used to build, train, test, tune, and publish AI-ML models easily and instantly. rubiML offers interactive data exploration. Thus, it becomes easy to design and optimize AI-ML models and it boosts analytical productivity without any knowledge of coding.
In rubiML, predictive modeling is performed using ML (supervised or non-supervised). Operations like regression, classification, and clustering are performed in rubiML.
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rubiPython is an option within code fusion on the rubiscape platform, where users can write their codes using the Python programming language, while building models. It is a custom code component that can be used to add Python code to form event and customize the model through Python code.
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rubiR is an option within code fusion on the rubiscape platform, where users can write their codes using R programming language, while building models.
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rubiscape is a new age data science platform that unleashes new values from data for enterprises, institutions, and individuals through co-creation and continuous innovation.
rubiscape provides a platform for developing, deploying, and managing real-time decision Application Programming Interfaces (APIs). The rubiscape architecture incorporates a powerful integration of Big data as well as an open-source ecosystem.
The mission of rubiscape is to help people connect their curiosity and experience with 'any data'. It aims to simplify Data Science through innovative tools and techniques.
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rubisight is a visual data storytelling dashboard with a simple drag-and-drop functionality. Once the model is ready, it can be displayed on the dashboard in rubisight.
rubisight is a cloud-powered visual data exploration experience. It enables business users achieve faster dashboard turnaround and provides flexibility in tapping data in any subject area (without the knowledge of coding), or any specific technical skills.
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rubistudio is a simple no-code or low-code drag-and-drop visual model builder. It is used to build, train, test, deploy and publish models, and reuse them whenever required. The uniqueness of rubistudio is that it makes the process seamless. Data scientists can maintain multiple versions of models, integrate Python and R based models, and customize coding.
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rubitext combines the power of AI, ML, and Natural Language Processing to identify, mine, parse, categorize, cluster, and model textual data.
rubitext has a powerful built-in engine that simplifies word frequency analysis, pattern recognition, tagging/annotation, information extraction, link and association analysis, and predictions to extract deeper insights.
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rubithings provides connected intelligence and enriches the data experience for smart maximization of value by inter-networking of physical devices, vehicles, buildings, machines, electronics, software, and sensors with IoT and M2M applications.
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rubiscape
The mission of data science is to understand and analyse actual phenomena with the help of data. At rubiscape, an agile data science methodology called rubiwise is developed.
rubiwise is crafted out of the design-thinking principles of rubiscape. Rubiwise is created with the mission to simplify data science through effective strategies. These are datasets (diverse sources and infrastructures), skillsets (talents and creativity), toolsets (rubiscape and open source), and mindsets (principles and ethos) to innovate and deliver a value.
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rubiscape
Template file is a customized sample file used to store data in an optimized manner. It is vital in the development and testing phases.
It is used to store target data into a CSV file. These files are stored locally or on cloud, that is, places which are designated for storing all the log files.
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The template table is a customized sample table used to store data in an optimized manner. It is vital in the development and testing phases.
It is used to create target RDBMS datasets. The properties section provides you the facility to select from the available RDBMS data sources and its tables.
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Writer contains the template table and the template files.
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