Machine learning (ML) has permeated virtually every sector, revolutionizing processes, enhancing efficiency, and unlocking insights. The proposed system provides a kit for all the analysis steps that must be performed on the data before applying the Machine Learning tools. It can provide ease to the industry where the data scientist and data analysis jobs can focus more on the models and refining them instead of cleaning and augmenting data. The proposed system is aimed for data analysis and prediction jobs automation by providing ease in doing the steps for data prediction. The system provides an intuitive and accessible user interface for users with varying technical backgrounds which provides comprehensive functionality with automated tools for data preprocessing, diverse machine learning algorithms, and innovative visualizations. Transparency in the data cleaning process addressed fosters user trust and control over data manipulation is also presented in this paper. The proposed system is designed and dedicated to budding data analytics and students.

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Interactive Frontend Analyzer Tool for Machine Learning Pipeline

  • J. Dhiviya Rose,
  • Advait Dhakad,
  • Chirag Yadav,
  • Rishi Madan,
  • Khushi Gupta

摘要

Machine learning (ML) has permeated virtually every sector, revolutionizing processes, enhancing efficiency, and unlocking insights. The proposed system provides a kit for all the analysis steps that must be performed on the data before applying the Machine Learning tools. It can provide ease to the industry where the data scientist and data analysis jobs can focus more on the models and refining them instead of cleaning and augmenting data. The proposed system is aimed for data analysis and prediction jobs automation by providing ease in doing the steps for data prediction. The system provides an intuitive and accessible user interface for users with varying technical backgrounds which provides comprehensive functionality with automated tools for data preprocessing, diverse machine learning algorithms, and innovative visualizations. Transparency in the data cleaning process addressed fosters user trust and control over data manipulation is also presented in this paper. The proposed system is designed and dedicated to budding data analytics and students.