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arunsinghbabal/README.md
  • 👋 Hi, I’m Data Scientist with a strong background in statistics, machine learning, and data analysis. Proficient in programming languages such as Python and R, with experience in implementing various algorithms and models to extract insights from complex data sets. Keen attention to detail and a passion for finding solutions to complex problems. Currently exploring new technologies and methodologies to stay up-to-date with industry advancements. Check out my GitHub repository for more information on my projects and expertise.

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  1. Traffic-Security Traffic-Security Public

    The goal of the project is to classify the vehicles, count their frequency, track them using unique ID and provide safety measures to the users by flagging the suspicious ones.

    Python 12 3

  2. Banking-System-Database-Management Banking-System-Database-Management Public

    A small scale relica of bank management system using the MySQL queries in the python language.

    Jupyter Notebook 2

  3. Automated-Defective-Substrate-Identification-for-Expedited-Manufacturing Automated-Defective-Substrate-Identification-for-Expedited-Manufacturing Public

    Identifies the faulty wafer before it can be used for the fabrication of integrated circuits and, in photovoltaics, to manufacture solar cells. The project retrains itself after every prediction, m…

    Python 7 1

  4. Controlled-Automation-for-Data-Processing Controlled-Automation-for-Data-Processing Public

    Perform semi automated exploratory data analysis, feature engineering and feature selection on provided dataset by visualizing every possibilities on each step and assisting the user to make a mean…

    Jupyter Notebook 5

  5. Time-Series-Predictive-Analytics-for-Hair-Device Time-Series-Predictive-Analytics-for-Hair-Device Public

    Stable temperature is ideal for hair styling, this framework successfully predicts the future power output (correlated with the temperature) based on the historical data to reduce the time lag.

    Jupyter Notebook 2

  6. Click_through_vs_conversion_classification Click_through_vs_conversion_classification Public

    The model classifies the advertisements by clicked or not-clicked and later identifies zero, low or high conversion rate.

    Jupyter Notebook 3